@article{ author = {}, title = {Image Encryption Algorithm based on Recursive Cellular Automata}, abstract ={In this paper, a new structure for image encryption using recursive cellular automatais presented. The image encryption contains three recursive cellular automata in three steps, individually. At the first step, the image is blocked and the pixels are substituted. In the next step, pixels are scrambledby the second cellular automata and at the last step, the blocks are attachedtogether and the pixels substitute by the third cellular automata. Due to reversibility of cellular automata, the decryption of the image is possible by doing the steps reversely. The experimental results show that the encrypted image is not comprehend visually, also this algorithmhas satisfactory performance in terms of quantitative assessment from some other schemes.}, Keywords = {Cryptography, Cellular Automata, Recursive Cellular Automata}, volume = {13}, Number = {1}, pages = {3-14}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-266-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-266-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {khorashadizadeh, majid and latif, ali mohamm}, title = {image denoising using adaptive switching filter based on extreme learning machine}, abstract ={In this paper a new efficient method for detecting the impulse noise from the corrupted image using extreme learning machine (ELM) is proposed. An improved version of the standard median filter is suggested to remove the detected noisy pixel. The performance of proposed detector is evaluated using classification accuracy. The results show that our detector is robust even at higher noise density. Results illustrate that proposed filter provides better performance in terms of PSNR than many other median filter variants for Salt and pepper noise. . The suggested technique yields significantly good results both in objective and subjective judgments of image quality.}, Keywords = {}, volume = {13}, Number = {1}, pages = {15-25}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-294-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-294-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {RezaeiSharifabadi, Morteza and Khosravizadeh, Parvaneh}, title = {Automatic Labeling of Semantic Roles in Persian Sentences using Dependency Trees}, abstract ={Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and therefor the syntactic representation chosen affects the overall performance of the system. In this research, we present a semantic role labeling system based on full syntactic parsing. For this purpose, we use a dependency parser and machine learning methods. In our system, we have made an effort to overcome the problems of previous semantic role labelers for Persian, which all are based on shallow syntactic parsing. The outcome of the system is promising.}, Keywords = {semantic role labeling, shallow semantic parsing, dependency grammar, Persian language, natural language processing, computational linguistics}, volume = {13}, Number = {1}, pages = {27-38}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-279-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-279-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Ansari, Zohreh and Seyyedsalehi, Ali}, title = {Deep Modular Neural Networks with Double Spatio-temporal َAssociation Structure for Persian Continuous Speech Recognition}, abstract ={In this article, growable deep modular neural networks for continuous speech recognition are introduced. These networks can be grown to implement the spatio-temporal information of the frame sequences at their input layer as well as their labels at the output layer at the same time. The trained neural network with such double spatio-temporal association structure can learn the phonetic sequence subspace. Therefore, it can filter out invalid phonetic sequences in its own structure and output valid sequences. To evaluate the performance of these growable neural networks, we used FARSDAT and BIG FARSDAT datasets. Experimental results on FARSDAT show that deep modular neural networks outperform the phone accuracy rate of GMM-HMM models with an absolute improvement of 2.7%. Moreover, developing deep modular neural networks to a double spatio-temporal association structure improves their result by 5.1%. As there is no phonetic labeling for BIG FARSDAT, a semi-supervised learning algorithm is proposed to fine-tune the neural network with double spatio-temporal structure on this dataset, which achieves a comparable result with HMMs.}, Keywords = {Deep neural networks, Modular neural networks, Pre-training, Semi-supervised learning, Continuous speech recognition}, volume = {13}, Number = {1}, pages = {39-56}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-277-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-277-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Shekofteh, Yasser and Gholipor, Hasan and Goodarzi, M.Mohsen and kabudian, Jahanshah and Almasganj, Farshad and Reza, Shaghayegh and Sarraf, Im}, title = {Fast estimation of warping factor in the vocal tract length normalization using obtained scores of gender detection modeling}, abstract ={The performance of automatic speech recognition (ASR) systems is adversely affected by the variations in speakers, audio channels and environmental conditions. Making these systems robust to these variations is still a big challenge. One of the main sources of variations in the speakers is the differences between their Vocal Tract Length (VTL). Vocal Tract Length Normalization (VTLN) is an effective method introduced to cope with this variation. In this method, the speech spectrum of each speaker is frequency warped according to a specific warping factor of that speaker. In this paper, we first developed the common search-based method to obtain the appropriate warping factor over a HMM-based Persian continuous speech recognition system. Then pointing out the computational cost of search-based method, we proposed a linear regression process for estimating warping factor based on the scores generated by our gender detection system. Experimental results over a Persian conversational speech database shown an improvement about 0.54 percent in word recognition accuracy as well as a significant reduction in computational cost of estimating warping factor, compared to search-based approach.}, Keywords = {speech recognition, Vocal Tract Length Normalization, gender detection, linear regression, warping factor,}, volume = {13}, Number = {1}, pages = {57-70}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-254-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-254-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Ahangarbahan, Hamid and Montazer, Gholam Ali}, title = {Design a Sentence Based Plagiarism Detection System by Evidences Fusion in Persian Text}, abstract ={Today, there are many documents on Internet, such that users can generate new documents by coping them and existing Plagiarism Detection systems (PDS) couldn't detect all kind of plagiarism. The main challenge is finding a suitable algorithm to improving the amount of similar documents and their assessing time. It’s difficult to do assessing similarity in Persian texts that different characteristics affect on it and also many of them are ambiguous. For this reason Dempster - Shefer (Evidence) theory has been used in this paper. The proposed system will assess in a two-level and in the first stage, sentences will divide in general and expert terms and then assessing by suitable measures and domain ontology. These results will be delivered to first level as "basic belief" and will be integrated by using a Dempster combination rule to create one of the second level inputs. In second level, the previous level result and another similarity measures will be weighted and combined belief and plausibility functions for final assessment will be distinguished. This system has been used for real data assessment and compared the actual results shows that the precision between the system results and actual results is about 90%, which implies that the system can be used as Plagiarism Detection System.}, Keywords = {Plagiarism, Data fusion, Evidence theory, Similarity Measures, Semantic Similarity}, volume = {13}, Number = {1}, pages = {71-85}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-276-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-276-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {}, title = {Improved Clustering Persian Text Based on Keyword Using Linguistic and Thesaurus Knowledge}, abstract ={Persian words in writing with a diverse and cover all modes of grammatical words with the recruitment of a series of specific rules because it is impossible to extract keywords automatically from Persian texts difficult and complex. This thesis has attempted to use linguistic information and thesaurus, keywords Mnatry be provided. Using the symbol system is structured network can be keywords, including the exchange of words, words and words with hierarchical relationships complete the package has increased. Therefore the agreement between users and search keywords text search and recall is increased. In the first stage non-important words are removed and the public. Supervision in the text are words and more words to clarify the relative importance of using a blower numerical weight is assigned to each word that indicates the effectiveness of the word in connection with the subject and compared with the other words used in the text. Particularly complex operation that makes use of thesaurus keywords are extracted Mnytry that kind of hierarchical category scientific literature in the field of information retrieval is indicated. Test results on different topics several text accurately represents the proposed method and the ability to extract the keywords in accordance with user demand.}, Keywords = {Keyword Extraction, Thesaurus, Computational Linguistic, Information Retrieval}, volume = {13}, Number = {1}, pages = {87-100}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-139-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-139-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Ahmadizar, Fardin and Soltanian, Khabat and AkhlaghianTab, Fardi}, title = {Construction and Training of Artificial Neural Networks using Evolution Strategy with Parallel Populations}, abstract ={Application of artificial neural networks (ANN) in areas such as classification of images and audio signals shows the ability of this artificial intelligence technique for solving practical problems. Construction and training of ANNs is usually a time-consuming and hard process. A suitable neural model must be able to learn the training data and also have the generalization ability. In this paper, multiple parallel populations are used for construction of ANN and evolution strategy for its training, so that in each population a particular ANN architecture is evolved. By using a bi-criteria selection method based on error and complexity of ANNs, the proposed algorithm can produce simple ANNs that have high generalization ability. To assess the performance of the algorithm, 7 benchmark classification problems have been used. It has then been compared against the existing evolutionary algorithms that train and/or construct ANNs. Experimental results show the efficiency and robustness of the proposed algorithm compared to the other methods. In this paper, the impact of parallel populations, the bi-criteria selection method, and the crossover operator on the algorithm performance has been analyzed. A key advantage of the proposed algorithm is the use of parallel computing by means of multiple populations.}, Keywords = {Artificial Neural Networks, Evolution Strategy, Parallel Populations}, volume = {13}, Number = {1}, pages = {101-114}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-110-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-110-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {}, title = {Hyperspectral Images Sub-Pixel Classification Based on Pixel-Swapping Algorithm Extension and Its Evaluation}, abstract ={The capability of the matter identification is developed considerably in hyperspectral images. The spectral reflectance of surfaces in these imaging systems in the visible and near infrared range of the electromagnetic spectrum is recorded in extremely narrow and continuous bands. But for some reasons, such as existence the mixed pixels and low spatial resolution of these images, is difficult to land cover accurate position identify. The soft classification methods provide the estimation of the membership value of various classes within mixed pixels. But, by using these methods, the matter information extraction is possible only and position information extraction in sub-pixel level is impossible. In recent years, in order to solve this problem, some methods that are called SRM, have been developed for positioning the extracted membership values by soft classification process in sub-pixels for producing a higher spatial resolution land use map. In this paper, pixel-swapping method is used as the latest SRM algorithms, and with repetition the binary case of this algorithm for each class, this algorithm has been generalized and developed for multi-class. Another main point in sub-pixel classification is the performance evaluation of these classifiers. Because of the influence of various parameters in the sub-pixel classification, the evaluation of this process is very complex. Hence, as a main and innovative activity in this paper, the Influence of the neighborhood level and the zoom factor as two important parameters in the extension pixel-swapping method has been simulated and analyzed. For this purpose, in this paper a framework for evaluating the sub-pixel classification performance based on dependent on and independent on soft classification error is proposed.}, Keywords = {Hyperspectral image, Sub-pixel classification, Sub-pixel classification evaluation, Pixel-swapping method, SRM algorithm}, volume = {13}, Number = {1}, pages = {115-125}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-30-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-30-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Zardadi, Mohsen and Mehrshad, Naser}, title = {A New Approach to Retinal Vessel Segmentation by Using Computational Model of Simple Cells in Primary Visual Cortex}, abstract ={In this paper, a new unsupervised algorithm for automatic retinal blood vessel extraction is presented. A pre-processing step is introduced to eliminating optic disk and back ground noise. Blood vessel highlighting is prepared by a new method inspired by simple cells in human visual system. An adaptive threshold is introduced as an activation function of simple cells. Post-processing step is used as a final stage at the output of simple cells to eliminating exudates which is detected as blood vessels. The results on DRIVE database demonstrate that the performance of the proposed algorithm is comparable with state-of-the-art techniques in terms of execution time and extracted vessels.}, Keywords = {retinal vessel segmentation, medical assistance systems, retinal simple cell model, DRIVE database }, volume = {13}, Number = {1}, pages = {127-138}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-230-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-230-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Farhang, Mohsen and Bahramgiri, Hosein and Dehghani, Hami}, title = {Novel Features for Modulation Recognition Using an 8PSK Demodulator}, abstract ={In this paper a feature-based modulation classification algorithm is developed for discriminating PSK signals. The candidate modulation types are assumed to be QPSK, OQPSK, π/4 DQOSK and 8PSK. The proposed method applies an 8PSK baseband demodulator in order to extract required features from observed symbols. The received signal with unknown modulation type is demodulated by an 8PSK demodulator whose output is considered as a finite state machine with different states and transitions for each candidate modulation. Estimated probabilities of particular transitions constitute the discriminating features. The obtained features are given to a Bayesian classifier which decides on the modulation type of the received signal. The probability of correct classification is computed with different number of observed symbols and SNR conditions by carrying out several simulations. The results show that the proposed method offers more accurate classification compared to previous methods for classifying variants of QPSK.}, Keywords = {automatic modulation classification, feature extraction, pattern recognition, variants of QPSK, Bayes classifier.}, volume = {13}, Number = {2}, pages = {3-10}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-70-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-70-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Moradi, Ali and Shahbahrami, Asadollah and EbrahimiAtani, Reza and AlidoustNia, Mehr}, title = {Persian XML Documents Metaheuristic Clustering Based on Structure and Content Similarity}, abstract ={Due to the increasing number of documents, XML, effectively organize these documents in order to retrieve useful information from them is essential. A possible solution is performed on the clustering of XML documents in order to discover knowledge. Clustering XML documents is a key issue of how to measure the similarity between XML documents. Conventional clustering of text documents using a document similarity measure used in information content, they can cause structural information contained in XML documents is ignored. In this paper, a new model named matrix space model to represent both structural and content features of documents in XML, is proposed. Based on this model, the Jaccard similarity measure is defined and the colonial competitive algorithm for clustering XML documents is used. Experimental results show that the proposed model function in identifying similar documents which closely identified with the same structure and content information are effective. This method can improve the accuracy of clustering, and XML data can be used to increase productivity.}, Keywords = {Clustering, Persian, colonial competitive algorithm, }, volume = {13}, Number = {2}, pages = {11-23}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-29-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-29-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {khalilzadeh, mohammad ali and dustdarnughabi, hojjat}, title = {Evaluation of blood perfusion of the trapezius muscle with wavelet analysis of photoplethysmogram signal using neural network}, abstract ={Measurement of tissue blood perfusion has many applications in the prevention of pressure sores, muscle activity assessment and care of tissue blood perfusion during surgery. Photoplethysmography as a continuous measure for evaluation of blood perfusion in tissue is accepted by researchers. In this study a new method for assessment of blood perfusion to the tissue based on photoplethysmograph signal (PPG) is presented. Wavelengths of the PPG were near infrared 950 nm with source-to-detector separation of 7 and 22 mm. The probe was placed over the trapezius muscle of 19 healthy subjects under the external pressures of 0 and 40 and 80 mmHg. PPG envelope detected and wavelet transform calculated in the five frequency intervals. These bands relate to metabolic, neurogenic, myogenic, respiratory and cardiac activities. The p-value of the t-test analysis for extracted features was less than 0.005. Results have shown that by applying external pressure, tissue deep layers most affected and the amount of their blood perfusion is reduced. Accuracy of separation at different pressures for back propagation neural network (BPNN) was 73.68% and for generalized regression neural network (GRNN) was 79.6%. Improvement of this method can be as a clinical assessment of tissue blood perfusion and can be as an effective method in prevention of pressure ulcers.}, Keywords = {Blood perfusion, Photoplethysmogram, Wavelet transform, generalized regression neural network (GRNN)}, volume = {13}, Number = {2}, pages = {25-33}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-253-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-253-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Noferesti, Samira and Shamsfard, Mehrnoush}, title = {Automatic building a corpus and exploiting it for polarity classification of indirect opinions about drugs}, abstract ={Opinion mining is a well-known problem in natural language processing that has attracted increasing attention in recent years. Existing approaches have been often focused on identifying direct opinions and ignored indirect ones. However, in some domains such as medical, indirect opinions occur frequently. Therefore, ignoring indirect opinions can lead to the loss of valuable information and noticeable decline in overall accuracy of opinion mining systems. In this paper, we present a semi-automatic approach to construct a corpus of indirect opinions from drug reviews. In the first step, we propose an automatic method for detection of indirect opinions and in the second step, we use domain knowledge, linguistic rules and review structure for polarity detection of drug reviews. Then we exploit the constructed corpus as a training set in machine learning techniques for polarity classification of new examples. Experimental results demonstrate that our proposed approach achieves 82.81 percent precision.}, Keywords = {opinion mining, indirect opinions, sentiment analysis, corpus construction, machine learning}, volume = {13}, Number = {2}, pages = {35-49}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-299-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-299-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {hamidi, hodjat}, title = {An Approach to protecting of data processing system in computing systems using convolutional code}, abstract ={Abstract We present a framework for algorithm-based fault tolerance methods in the design of fault tolerant computing systems. The ABFT error detection technique relies on the comparison of parity values computed in two ways. The parallel processing of input parity values produce output parity values comparable with parity values regenerated from the original processed outputs. Number data processing errors are detected by comparing parity values associated with a convolution code. This article proposes a new computing paradigm to provide fault tolerance for numerical algorithms. The data processing system is protected through parity values defined by a high-rate real convolution code. Parity comparisons provide error detection, while output data correction is affected by a decoding method that includes both round-off error and computer-induced errors. To use ABFT methods efficiently, a systematic form is desirable. A class of burst-correcting convolution codes will be investigated. The purpose is to describe new protection techniques that are easily combined with data processing methods, leading to more effective fault tolerance.}, Keywords = {algorithm-based fault tolerance (ABFT),convolution codes, parity values, syndrome}, volume = {13}, Number = {2}, pages = {51-69}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-349-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-349-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Asgharian, Lida and ebrahimnezhad, Hossei}, title = {Animating of Carton Characters by Skeleton based Articular Motion Transferring of Other Objects}, abstract ={Abstract: Nowadays, the animators give life to the fancy characters by making natural movements to organs of cartoon characters. To achieve this goal, movements of living individuals can be applied into cartoon characters. In this paper, a skeletal correspondence finding based method is proposed to transfer movement of a 2D character into a new character, where these two shapes have the same structural topology, approximately. Based on the given animation sequence of source character, each body part of this character is segmented according to a specific motion. In this case, an exact skeleton with defined joints will be achieved for source shape. The target character skeleton is obtained by automatic skeleton extraction algorithms. In this stage, by skeletal correspondence finding between source and target character, we can transfer skeleton deformation of each source body parts into target body parts. This deformation contains the values of skew, scale and orientation that are achieved from reference pose and deformed poses of source skeletons. Finally, to evaluate the proposed method efficiency, we perform it on 2D animation characters. The achieved results illustrate the ability of the algorithm in generating correct and natural motions for different variety of characters. The method is robust to the type of characters and can transfer variety of deformations.}, Keywords = {Motion retargeting, Animation, Skeleton correspondence, Joint extraction}, volume = {13}, Number = {2}, pages = {71-89}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-312-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-312-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {sharifnoughabi, mojtaba and marvi, hossein and darabian, danial}, title = {Farsi Accent Recognition based on speech signal using efficient features extraction and Combining of Classifiers}, abstract ={Speech recognition has achieved great improvements recently. However, robustness is still one of the big problems, e.g. performance of recognition fluctuates sharply depending on the speaker, especially when the speaker has strong accent and difference Accents dramatically decrease the accuracy of an ASR system. In this paper we apply three new methods of feature extraction including Spectral Centroid Magnitude (SCM), its first order difference (∆SCM ) and Zak transformation to the original speech signal using accents selected from FARSDAT corpus then their performance of these methods have been compared with some common methods such as MFCC. Moreover a new feature based on MFCC algorithm have been proposed in order to use in noisy environments. Five different classifications, including MLP, KNN, PNN, RBF and SVM and their combination have been used to evaluate the performance of each feature extraction methods. Experimental results demonstrate improvement in the recognition rates in our proposed method.}, Keywords = {Spectral Centroid Magnitude, classifiers combination, Farsi accents, support vector machine, Improved Mel Frequency Cepstral Coefficient}, volume = {13}, Number = {2}, pages = {91-103}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-315-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-315-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Asadi, Sekine}, title = {Providing a method for image preprocessing to improve the performance of JPEG}, abstract ={A lot of researchs have been performed in image compression and different methods have been proposed. Each of the existing methods presents different compression rates on various images. By identifing the effective parameters in a compression algorithm and strengthen them in the preprocessing stage, the compression rate of the algorithm can be improved. JPEG is one of the successful compression algorithm that various works have been done to improve its performance. Image contrast is one important factor affecting on JPEG compression rate. The lower the image contrast, the less detail is visible and JPEG will be able to compress such images with a higher rate. In this paper, a semi-lossless preprocessing method based on power operator is proposed that decreases the image contrast by reducing the range of graylevels in the image. Therefore, JPEG can compress the preprocess images with a higher compression ratio. To restore the image, after decoding the compressed image, by applying the inverse exponent value to the power operator on this image, an image similar to the original image will be achieved. The results show that the proposed preprocessing method substantially increases the JPEG compression ratio on natural images.}, Keywords = {Preprocessing, Image compression, Semi-lossless, JPEG method.}, volume = {13}, Number = {2}, pages = {105-120}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-320-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-320-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Dehghan, Mohammad Hossein and Faili, Heshaam}, title = {Generating the Persian Constituency Treebank in an Automatic Converting Method}, abstract ={Treebanks is one of important and useful resource in Natural Language Processing tasks. Dependency and phrase structures are two famous kinds of treebanks. There have already made many efforts to convert dependency structure to phrase structure. In this paper we study an approach to convert dependency structure to phrase structure because of lack of a big phrase structure Treebank in Persian. Also we study the algorithm’s errors and propose a solution to solve the problem and improve the quality of conversion process. The experiment results show that we can improve the quality of conversion, about 25.85 percent, in Persian and about 4.39 percent in English. With the help of the conversion algorithm and the dependency Treebank, we produce the phrase structure treebank and train a parser using the resulted treebank. Our parser output is about 21 percent, better than the same parser introduced as baseline.}, Keywords = {Natural Language Processing, Persian Language, Dependency Structure Treebank, Phrase Structure Treebank, Phrase Structure Parser}, volume = {13}, Number = {2}, pages = {121-137}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-336-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-336-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {ShafeipourYourdeshahi, Sajjad and Seyedarabi, Hadi and Aghagolzadeh, Ali}, title = {Video based Face Recognition Using Orthogonal Locality Preserving Projection}, abstract ={In this paper, attempting to improve the recognition rate and solve some problems such as pose, lighting variations and partial occlusion in video sequences using Orthogonal Locality Preserving Projection (OLPP). In this research, first of all face in video frames is detected for background removing. Then each set of images is distributed on a nonlinear manifold and clustered using appropriate methods then the center of each cluster is considered as the cluster representative. It is also shown that by using OLPP the key frames are projected to the new space, where the frames in each manifold are better closed also the frames in different manifold are better separated. The recognition is done by projecting the test video sequence to the new space and calculating the distance between manifolds. Comparing the experimental results of the proposed method with other methods demonstrate the effectiveness of the proposed approach.}, Keywords = {face recognition, Orthogonal Locality Preserving Projection, key frame, subspace, manifold}, volume = {13}, Number = {2}, pages = {139-149}, publisher = {Research Center on Developing Advanced Technologies}, url = {http://jsdp.rcisp.ac.ir/article-1-340-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-340-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Ghassemian, Hassan and Hosseini, Seyed Abolfazl}, title = {Hyper-Spectral Data Feature Extraction Using Rational Function Curve Fitting}, abstract ={In this paper, with due respect to the original data and based on the extraction of new features by smaller dimensions, a new feature reduction technique is proposed for Hyper-Spectral data classification. For each pixel of a Hyper-Spectral image, a specific rational function approximation is developed to fit its own spectral response curve (SRC) and the coefficients of the numerator and denominator polynomials of this function are considered as new extracted features. The method focuses on geometrical nature of SRCs and relies on the fact that the sequence discipline - ordinance of reflectance coefficients in spectral response curve - contains some information which has not been addressed by many other existing methods based on the statistical analysis of data.  Maximum likelihood classification results demonstrate that our method provides better classification accuracies in comparison with many competing feature extraction algorithms. In addition, the proposed algorithm has the possibility  of being  applied to all pixels of image individually and simultaneously as well. }, Keywords = {}, volume = {13}, Number = {3}, pages = {3-16}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.3}, url = {http://jsdp.rcisp.ac.ir/article-1-346-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-346-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {SadeghiBajestani, Ghasem and Monzavi, Abbas and HashemiGolpaygani, Seyed Mohamad Rez}, title = {Precisely chaotic models survey with Qualitative Bifurcation Diagram}, abstract ={The most important method  for behavior recognition of recurrent maps is to plot bifurcation diagram. In conventional method used for plotting bifurcation diagram,  a couple of time series for different values of model parameter have been generated and these points have been plotted with due respect to it after transient state. It does not have enough accuracy necessary for period detection and essential for discrimination between long periodic behaviors from chaotic behaviors; on the other hand because of being 2-dimensinal, it will not be possible to investigate the effect if the initial condition is in the basin of attraction. In this research, a new bifurcation diagram is presented which is called: Qualitative Bifurcation Diagram (QBD). QBD provides accurate determination of periodicity. Results of our algorithm implementation on logistic map, represents its ability on determining long periods and period windows. Bifurcation diagram of logistic map does not obey mosaic tiling patterns (patterns that are created by arrangement not interaction) as a disciplinein addition to having the dynamic order. Some benefits of QBD are: long period discrimination, period window detection, computation time reduction, period presentation instead of amplitude show. In the  following we have an analytical survey to Lyapunov exponent – as a usual measurement tool for chaotic behavior – and important notes are expressed. Finally, Recurrent Quantification Analysis (RQA) and QBD are compared.  }, Keywords = {Bifurcation diagram, Chaos, Logistic Map, Lyapunov Exponent, Recurrent Quantification Analysis}, volume = {13}, Number = {3}, pages = {17-34}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.17}, url = {http://jsdp.rcisp.ac.ir/article-1-309-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-309-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Mahdikhanlou, Khadijeh and Ebrahimnezhad, Hossei}, title = {Shape based object retrieval using descriptors extracted from growing contour process}, abstract ={In this paper, a novel shape descriptor for shape-based object retrieval is proposed. A growing process is introduced in which a contour is reconstructed from the bounding circle of the shape. In this growing process, circle points move toward the shape in normal direction until they  get to the shape contour. Three different shape descriptors are extracted from this process: the first descriptor is defined as the number of steps that every circle point should pass which is called Growing Steps. The second descriptor is considered as the boundary distance of the circle points at the end of the growing process. The third descriptor is the curvature of the growing lines created by moving points. Invariance to translation is the intrinsic property of these features. By selecting a fixed starting point and tracing the boundary in a fixed direction (clock-wise or  counter clock-wise), a set of descriptors  could be collected invariant to rotation. Finally, normalizing the descriptors makes them invariant to scale. Support vector machines based on one-shot score are applied in the retrieval stage. Experimental results show that the suggested method has high performance for shape retrieval. It achieves 89.16% retrieval rate on MPEG-7 CE-Shape-1 dataset.}, Keywords = {Shape retrieval, Growing points, Growing steps, Boundary distance, Curvature of growing lines, SVM-OSS.}, volume = {13}, Number = {3}, pages = {35-50}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.35}, url = {http://jsdp.rcisp.ac.ir/article-1-358-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-358-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {BabaAli, Bagher}, title = {}, abstract ={Although researches in the field of Persian speech recognition  claim  a  thirty-year-old  history in Iran  which has achieved considerable progresses, due to the lack of well-defined experimental framework, outcomes from many of these researches are not comparable to each other and their accurate assessment won’t be possible. The experimental framework includes ASR toolkit and speech database which consists of training, development and test datasets. In recent years,   as a state-of-the-art open-source ASR toolkit; Kaldi has been very well-received and welcomed in the community of the world-ranked speech researchers around the world. considering all aspects, Kaldi is the best option among all of the other ASR toolkits to establish a framework to do research in all languages, including Persian. In this paper, we chose Fardat as the speech database which is the counterpart of TIMIT for Persian language because not only it has got a standard form  but it’s also accessible for all researchers around the world. Similar to the recipe on TIMIT database, we defined these three sets on the Farsdat: Training, Development and Test sets. After a survey on Kaldi’s components and features, we applied most of state-of-the-art ASR techniques in the Kaldi on the Farsdat based on three sets definition. The best phone error rate on development and test set have been 20.3% and 19.8%. All of the codes and the recipe that was written by author have been submitted to Kaldi repository and they are accessible  for free, so all the reported results  will be easily replicable if you have access to Farsdat database.}, Keywords = {Persian Continuous Speech Recognition, FarsDat Database, Kaldi Toolkit}, volume = {13}, Number = {3}, pages = {51-62}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.51}, url = {http://jsdp.rcisp.ac.ir/article-1-348-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-348-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Moradi, Bahare and Ezoji, Mehdi}, title = {A Dynamic Skin Detection Method Using the Fusion of 2-D Histogram-Based Features}, abstract ={This paper presents a dynamic approach to Skin Detection- to separate the skin pixels from non-skin pixels- in colored images. The static methods which use a fixed skin color model, will fail if there are illumination variations or different skin colors in an image. Because of contextual information the proposed algorithm will be less sensitive to the uncontrolled illumination conditions. In addition, the selection of discriminant features and the fusion of them and Bayesian classification increase the accuracy of the proposed method in comparison to the reference methods.}, Keywords = {Skin Detection, Skin Dynamic model, 2-D Histogram, Bayesian Rule}, volume = {13}, Number = {3}, pages = {63-78}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.63}, url = {http://jsdp.rcisp.ac.ir/article-1-325-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-325-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {hanifelou, zahra and Monadjemi, Amir Hassan and moallem, peym}, title = {Robust method of changes of light to detect and track vehicles in traffic scenes}, abstract ={In this paper, according to the detection and tracking of the moving vehicles at junctions, a rapid method is proposed which is based on intelligent image processing. In the detection part, the Gaussian mixture model has been used to obtain the moving parts. Then, the targets have been detected using HOG features extracted from training images, Ada-boost Cascade Classifier and the trained SVM. At the tracking part, a number of key points on the image of the vehicle were identified at first. The center of mass of the object and the edges were used to obtain these key points because these points are primarily important and more common in tracking rigid bodies. Then, these points were tracked in consecutive frames using definitive adaptive procedures. Also, the Kalman filter has been used to estimate new locations when the detector  is not able to detect the targets. The major advantage of this method  in comparison with the previous methods is its resistance against vehicle's overlapping and changes in Illuminations, so that the detection accuracy is 90.80% on overloaded traffic scenes and 88.75% on the tracking vehicles.}, Keywords = {Detection, Tracking, Ada-boost, Kalman Filter, Vehicle tracking, Deterministic Methods Corresponding, Cost Function}, volume = {13}, Number = {3}, pages = {79-98}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.79}, url = {http://jsdp.rcisp.ac.ir/article-1-510-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-510-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {ghaemi, hadi and kahani, mohes}, title = {Question Classification using Ensemble Classifiers}, abstract ={Question answering systems are produced and developed to provide exact answers to the question posted in natural language. One of the most important parts of question answering systems is question classification. The purpose of question classification is predicting the kind of answer needed for the question in natural language. The  literature works can be categorized as rule-based and learning-based methods. This paper proposes a novel architecture for hybrid classification of questions. The results of the classifiers were combined by five methods of Weighted Voting, Behavior Knowledge space, Naive Bayes, Decision Template and Dempster-Shafer. The method uses a combination of two classifiers based on machine learning (Support Vector Machine and Sparse Representation) and one rule-based classifier. The learning-based classification uses the set of features extracted from the questions. The features are extracted on the basis of the lexical and syntactic structure of the questions. The results from the classifiers were combined by the methods that are common in the combination of one-class classifiers and the Obtained results indicate the improvement of the classification operations in comparison with the present methods. }, Keywords = {Question classification, Rule-based, Learning-based, Sparse Representation, Support Vector Machine, Question answering. }, volume = {13}, Number = {3}, pages = {99-112}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.99}, url = {http://jsdp.rcisp.ac.ir/article-1-270-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-270-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Saidi, Maryam and Mohammadian, Amin and Daneshikohan, Marzieh and Seyedsalehi, Zohreh}, title = {Automatic credibility assessment screening using discriminate analysis of skin conductance response and photoplethysmograph signals}, abstract ={Credibility assessment screening by a small system and receiving optimum result in minimum time is a basic need in critical gates. Therefore the aim of this research is automatic detection of stress in guilty persons through skin conductance response and photoplethysmograph signals which are convenient and ease-of-use sensors .In this paper, a set of database with interview protocol (including control and relevant questions) in mock crime (Stealing jewels) is provided. 40 subjects participated in the experiments. 28 time-frequency features are extracted from two mentioned signals. The function of dimension reduction algorithms including principal component analysis, Kernel based PCA, linear discriminant analysis, cluster based LDA is evaluated to select optimum features. Support Vector Machine, Bayesian and AdaBoost are used as classifiers. The evaluation of algorithms on database is based on LOO method. Maximum accuracy (81.08%) is obtained through principal components analysis as feature selection method and Bayesian as classifier.}, Keywords = {Stress detection, Screening, Skin conductance signal, Photoplethysmography.}, volume = {13}, Number = {3}, pages = {113-128}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.113}, url = {http://jsdp.rcisp.ac.ir/article-1-242-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-242-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Shahbahrami, Asadollah and Najafi, Kiumarc and Najafi, Tahereh}, title = {Different Application Fields of Brain Signal Processing in Iran}, abstract ={According to the researches, it turns out that human's activities are the results of the internal-neural activities of their brain. The reflection of such activities which are propagated throughout the scalp can then be acquired and processed. In this regard, brain signals can be acquired and recorded by EEG (Electroencephalography). Researchers have applied different technqiues for acquiring, pre-processing, feature extrcation and reduction and classifying EEG signal. According to published papers by Iranian researchers until 2015, it  has been found that most studies have been performed in medical applications and brain computer interface fields. Sampling and receiving EEG signals have been performed more in the central region than other regions. Statistical technqiues have more been used for feature extraction than other technqiues. Finally, the support vector machines are mostly used in the classification of brain signals. At the end, a study on anxiety and depression detection on fifty cases was performed in medical field. Simulation results show that our approach achieve an accuracy of up to 97 percents.}, Keywords = {Feature Extraction, Feature Reduction, Classification, Brain Signals}, volume = {13}, Number = {3}, pages = {129-154}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.129}, url = {http://jsdp.rcisp.ac.ir/article-1-305-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-305-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {Fayyazi, Hossein and Dehghani, Hamid and Hosseini, Mojtab}, title = {Sparse unmixing of hyper-spectral images using a pruned spectral library}, abstract ={Spectral unmixing of hyperspectral images is one of the most important research fields  in remote sensing. Recently, the direct use of spectral libraries in spectral unmixing is on increase. In this way  which is called sparse unmixing, we do not need an endmember extraction algorithm and the number determination of endmembers priori. Since spectral libraries usually contain highly correlated spectra, the sparse unmixing approach leads to non-admissible solutions. On the other hand, most of the proposed solutions are not noise-resistant and do not reach to a sufficiently high sparse solution. In this paper, with the purpose of overcoming the problems above, at first the spectral library will be pruned based on the spectral information of the image,clustering and classification techniques. Then a genetic algorithm  will be used for sparse unmixing. The experimental results on the simulated and real images show that the proposed method gives good results in noisy images. }, Keywords = {Hyper-spectral images, Spectral Library Pruning, Sparse Unmixing.}, volume = {13}, Number = {3}, pages = {155-169}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.3.155}, url = {http://jsdp.rcisp.ac.ir/article-1-128-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-128-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2016} } @article{ author = {BehzadFallahpour, Mojtaba and Dehghani, Hamid and JabbarRashidi, Ali and Sheikhi, Abbas}, title = {Modelling and Software Implementation of SAR Imaging System Performance in Spotlight Mode}, abstract ={SAR imaging systems are as a complement to passive remote sensing but the process of image formation in this systems is so complex So that the final image in the system is formed after the three basic steps: raw data acquisition, forming the signal space and image space. In addition, various factors within the system and outside the system are involved in the information that recorded by SAR, such as radar, platform, processing algorithm, imaging region and channel that each of them have many sub-parameters and this adds the complexity of the behavior of SAR. So due to the complexity, providing the model that describes how the SAR imaging system is highly important. In this paper, at first, the performance of the SAR image formation in spotlight mode placed on analytical modeling and after that the model comes in a soft implement. The implement includes three basic steps of image formation. So that raw data acquisition is done in CST and the signal and image formation are done in MATLAB software. This implementation provides a lot of abilities. So you can simulate the effect of the affect parameters in SAR images and better interpretation of themes. Also, the validity of the proposed solutions in electronic warfare or passive defense for SAR imaging systems can be studied by it.}, Keywords = {SAR, Signal Space, Image space, Scattering field, Functional model, Software Implementation }, volume = {13}, Number = {4}, pages = {3-18}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.3}, url = {http://jsdp.rcisp.ac.ir/article-1-377-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-377-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {zeinali, mansoor and ghasemian, hass}, title = {A novel method for increasing the spatial resolution of remote sensing images using lookup table}, abstract ={Different methods have been proposed to increase the image spatial resolution by mixed pixels decomposition. These methods can be divided into two groups. Some research have been attempted to obtain percentages of sub pixels and the other try to obtain their locations. These methods and their problems will be examined in this study. Common methods are reviewed with more emphasis. Finally, a new method for increasing the spatial resolution will be proposed to resolve some deficiencies of existing methods. Especially this method, instantly takes percentages and locations of mixed pixels end members without no use of additional information. This method applies a proper lookup table, which is derived from an input image. By defining a similarity metric function, we obtain a similar pixel for every input pixel. These similar pixels have equal sub pixel structures; hence, an input pixel will be decomposed to a proper set of sub pixels. In the high quality images, these sub pixels usually, belong to pure classes. This proposed method is examined on four sets of artificial and real data. First we degrade these data sets by averaging filtering, and then we restore degraded data, using this method and two other methods. One of these methods is a hard classification and the other is a combination of fuzzy c-means and direct method to obtain percentages and locations of sub pixels respectively. We obtain percent of correction classification and KAPPA criterions for these methods. Simulation results on artificial, real data show a good sub pixels decomposition performance of proposed method relative to those of other comparable methods. By particular, this method shows at least 7% of improvement in artificial and 2% in real data relative to other methods.  }, Keywords = {spatial resolution, change the image scale, lookup table, subpixel decomposition}, volume = {13}, Number = {4}, pages = {19-28}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.19}, url = {http://jsdp.rcisp.ac.ir/article-1-188-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-188-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {Esmaeili, Mohammad Reza and Zahiri, Seyed Hami}, title = {Epileptic seizure detection using Inclined Planes system Optimization algorithm(IPO)}, abstract ={Epilepsy is a neurological disorder after stroke. About 1 percent of people in the world are involved with this second most common neurological disorder. Epilepsy can affect people of different ages with an altered behavior or lack of patient awareness and affect one's social life. In 75% of cases, if epilepsy is diagnosed early and properly, it can be treated. Among all existing methods of analysis for the detection of epileptic brain activity, EEG is more applicable, due to its special features (including its low-cost and innocuous). Despite all the advantages of this method, the visual scoring of the EEG records by a human scorer is clearly a very time consuming and costly task considering the large number of epileptic patients admitted to the hospitals and the amount of data needs to be scored. Thus, a tremendous effort has been devoted by researchers towards automatic epileptic seizures detection in EEG. This paper offers a novel method based on heuristic and intelligent algorithms, inclined planes system optimization (IPO), to detect epileptic samples from healthy subjects. Like other heuristic algorithms, IPO is inspired by nature and its laws. How to move sphere objects on the slope without friction and their desire to reach the lowest point, shapes the main idea of the IPO. In the IPO, small balls like particles in the PSO are placed randomly on the search space. The balls search the search space to find the optimal point which is the lowest point (relative to a reference point) on the surface. In the current work, the data described by Andrzejak et al. was used; which contains 5 sets (Z, O, N, F and S). In this work, three different classification problems are created from the above dataset in order to compare the performance of our method with other approaches: In the first, two sets were examined, normal (set Z) and seizure (set S). In the second, four sets of the dataset were used and they were classified into two different classes: non-seizure (sets Z, N, F) and seizure (set S). In the third, all the EEGs from the dataset were used and they were classified into two different classes: sets Z, O, N and F are included in the non-seizure class and set S in the seizure class. The EEG signal under study is firstly decomposed into five sub-bands through DWT (D1–D4 and A4), and each sub-band represents different frequency bands information. Afterwards, four statistical parameters of maximum, minimum, average and standard deviation were calculated for each sub-band. And then, using the optimization algorithm IPO, the best weights are calculated to apply to the OVA classifier in order to find the best hyper plane separating the two classes. The fitness function defined in the IPO algorithm, is the number of signals that have been classified incorrectly. To classify EEG signals in three problems, the 10-fold Cross-Validation method is used. In this method, the data is divided into 10 subsections. And then, one subset is used for test and nine others for training. This procedure is repeated 10 times, until all the data is used for testing. The proposed algorithm have been implemented 10 times for the two wavelet functions Db1 and db2. Using the proposed method, the accuracy obtained for the three problems is 100%, 98/1%, 97/34%, respectively. Also by the proposed method diagnosis of epilepsy can be achieved very quickly. The results show that the algorithm is capable of detecting signals of epileptic and non-epileptic in less than 5 milliseconds. This makes it possible to use this method in real-time systems.}, Keywords = {Electroencephalogram(EEG), Epileptic seizure detection, Discrete wavelet transform(DWT), Heuristic algorithm, Inclined planes system optimization algorithm(IPO)}, volume = {13}, Number = {4}, pages = {29-42}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.29}, url = {http://jsdp.rcisp.ac.ir/article-1-238-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-238-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {VafaeiJahan, Maji}, title = {Feature Extraction of Computer Files Structure by Statistical Analysis}, abstract ={Files are the most important sources of information presenting in various formats such as texts, audio, video, images, web pages, etc. …; (in-depth) analysis of files for the purpose of recognition and investigating their unique properties (or characteristics) is one of the most significant issues in the field of personal security safety, information security, file-type identification, codes structuration analysis etc…. Statistical analytic methodology of working on the binary files contents based on the n-gram model has been opted for in the present paper in order to full investigate all different aspects of a file’s range of characteristics. Moreover, to reduce down the calculations volume and the n-gram model peculiar to the needed amount of memory, use has been made of word clustering. Later on analysis has been conducted on both files’ contents in two states of “blocking” and “full”: it is to be noted that in the “full” case such characteristics as Chi-square, Auto-correlation, Weighted term frequency-Inverse document frequency (TF-IDF), Fractal dimension etc … have been brought under comprehensive study; while in the “blocking” case, other properties like the entropy rate, the distance, etc … have been delved into. The gained results indicate that the extracted characteristics in the first method could well easily reflect the unique properties belonging to jpg, mp3, swf and html files; and in the second method, are able to clearly well reflect doc, html and pdf files properties.}, Keywords = {Files, n-gram model, word clustering, Canberra distance, entropy rate, Fractal dimension}, volume = {13}, Number = {4}, pages = {43-62}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.43}, url = {http://jsdp.rcisp.ac.ir/article-1-141-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-141-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {}, title = {Estimation of protein-coding regions in numerical DNA sequences using Variable Length Window method based on 3-D Z-curve}, abstract ={In recent years, estimation of protein-coding regions in numerical deoxyribonucleic acid (DNA) sequences using signal processing tools has been a challenging issue in bioinformatics, owing to their 3-base periodicity. Several digital signal processing (DSP) tools have been applied in order to Identify the task and concentrated on assigning numerical values to the symbolic DNA sequence, then applying spectral analysis tools such as the discrete Fourier transform (DFT) to locate the periodicity components. Despite of many advantages of Fourier transform in detection of exotic regions, this approach has some restrictions, such as high computational complexity and disability in locating the small length coding regions. In this paper, we improve the performance of the conventional DFT in estimating the protein coding regions utilizing a Gaussian window with variable length. First, the DNA strands are converted to numerical signals via the 3-D Z-curve method. Z curve is a robust, independent, less redundant approach, and has clear biological interpretation which can be regarded as a useful visualization technique for DNA analysis of any length. In the second stage, non-coding regions besides the background noise components are completely suppressed using the Gaussian variable length window. Also, we use a narrow-band band-pass filter in order to extract the period-3 components with  central frequency. Performance of the proposed algorithm is tested on F56F11.4 from C.elegans chromosome III, also two eukaryotic datasets, HMR195 and BG570,  is compared with other state-of-the-art methods based on the nucleotide evaluation metrics such as sensitivity, specificity, approximation correlation, and precision. Results revealed that, the area under the receiver operating characteristic (ROC) curve is improved from 4% to 40%, in HMR195 and BG570 datasets compared to other methods. Furthermore, the proposed algorithm reduces the number of incorrect nucleotides which are estimated as coding regions.   }, Keywords = {Protein Coding Regions, Period-3, Digital Signal Processing, DNA, Variable Length Window, Band-Limited Filter.}, volume = {13}, Number = {4}, pages = {63-78}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.63}, url = {http://jsdp.rcisp.ac.ir/article-1-101-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-101-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {ZohourParvaz, Farnaz and Fatemizadeh, Emad and Behnam, Hami}, title = {Speed improvement in graph-cuts-based registration for non-rigid image registration of brain magnetic resonance images}, abstract ={Image processing methods, which can visualize objects inside the human body, are of special interests. In clinical diagnosis using medical images, integration of useful data from separate images is often desired. The images have to be geometrically aligned for better observation. The procedure of mapping points from the reference image to corresponding points in the floating image is called Image Registration. It is a spatial transform. These images might be different because they were taken at different times or applied by using different devices. By the nature of this image transformation, image registration can be classified into rigid registration and non-rigid registration. The freedom’s degree in a rigid transformation is relatively low and the methods of rigid image registration are becoming mature. In contrast, non-rigid image registration is still a challenging problem because of its high degree of freedom. One of the non-rigid image registration methods is turning the registration problem into an optimization problem and obtaining the optimal value as the result of registration. An example of these methods is the graph-cuts based registration. The basic technique is to construct a specialized graph for the energy function to be minimized in a way that the minimum cut on this graph also minimizes the energy. Given that our focus in this research, is on the medical image registration, and time is one of the critical factors in medical applications. It seems that improvement of this method in terms of run time will be helpful for its clinical and medical applications. In order to achieve this goal, in this research, with modifying the energy function, we proposed a method that significantly reduces the run time of registration process. The implementation results of our proposed method on the images with artificial deformations which are similar to the most pessimistic possible deformation modes in real image data, show that the proposed algorithm is about three times faster than the existing algorithm, while the average amount of SAD criterion will be increased from 0.7 to 1.}, Keywords = {Non-rigid image registration, Graph-cuts, Magnetic resonance images}, volume = {13}, Number = {4}, pages = {79-92}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.79}, url = {http://jsdp.rcisp.ac.ir/article-1-252-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-252-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {dianat, rouhollah and ahmadi, morteza ali and akhlaghi, yahya and babaali, bagher}, title = {Introducing a new information retrieval method applicable for speech recognized texts}, abstract ={In this article a pre-processing method is introduced which is applicable in speech recognized texts retrieval task. We have a text corpus, t generated from a speech recognition system and a query as inputs,  to search queries in these documents and find relevant documents. A basic problem in a typical speech recognized text is some error percentage in recognition. This, results erroneously assigning to irrelevant documents.The idea of this proposed method, is to detect error-prone terms and to find similar words for each term. A parameter is defined which calculates the probability for occurring errors in the error-prone words. To recognize similar words for each specific term, based on a criterion called average detection rate (ADR) and levenshtein distance criterion, some candidates are chosen as the initial similar words set. And then, a conversion probability is defined based on the conversion rate (CR) and the noisy channel model (NCM) and the words with higher probability based on a threshold level are selected as the final similar words. In the retrieval process, these words are considered in the search step in addition to the base word.  Implementation result shows a significant improvement up to 30% of F-measure in information retrieval method with consideration of this pre-processing.}, Keywords = {Information retrieval, Speech recognition, Document, Query, Levenshtein Distance}, volume = {13}, Number = {4}, pages = {93-108}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.93}, url = {http://jsdp.rcisp.ac.ir/article-1-360-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-360-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {gharaee, hossein and mohammadi, fari}, title = {Modified AODV Routing Protocol in Order to Defend Wormhole Attacks}, abstract ={Mobile Ad hoc Networks (MANET) are vulnerable to both active and passive attacks. The wormhole attack is one of the most severe security attacks in wireless ad hoc networks, an attack that can be mounted on a wide range of wireless network protocols without compromising any cryptographic quantity or network node.  In Wormhole attacks, one malicious node tunnels packets from its location to the other malicious node. Such wormhole attacks result in a false route with fewer. If the source chooses this fake route, malicious nodes have the option of sniff, modify, selectively forward packets or them. Existing solution defends wormhole attacks, such as SECTOR, Packet Leashes, DelPHI, directional antenna. These solutions require special hardware or strict synchronized clocks or cause message overhead, or generate false-positive alarms. A novel approach MAODV: Modified AODV is proposed to defend wormhole attacks, launched in AODV. The proposed approach is based on weight per hop. Each node in network has its own weight, given by administration due to trusty power capability. Sum of weight will not be exceeded from 100. Whenever a source node wants to send a traffic to destination, puts its minimum weight in RREQ packet to constitute the route. The destination node is selected in the route that its weight is close to destination announcement weight. Since no special hardware and no encryption techniques are used, it is likely to have less overhead and delay, compared to other techniques. The proposed wormhole defend mechanism is discussed in detail. Our proposed system does not require any synchronized clocks or special hardware to defend wormhole attacks. In our proposed system some parameters will be added to AODV routing protocol and make it more secure against wormhole attacks. We will name this new protocol as MAODV. In the first place, there is a master node in network, which  weighs 100 (weighs of whole network). Whenever a node attends to enter the network, sends a join message to nearest neighbor. After receiving the message, master node will share its weights with the node requester, and sends the weight to this node requester. This process and weight sharing will be repeated after any requests to join a network, and total weight of network is not exceeded from 100. In our proposed method, each path which is created between source and destination, has a particular weight and this weight equals to intermediate node weights being added to each other. In MAODV whenever a source node wants to send RREQ packet, it adds the minimum weight to constitute route. After receiving RREQ packets, each intermediate node increases its weight beside increasing hop count. Each intermediate node does the same action, as far as destination node receives, RREQ packet among the received RREQ, one of them will be selected which its weight is the same as minimum requested weight by source, or slightly more than that. For instance, consider fig 1 which has 14 nodes. Assuming the node weights are equal for each node and its 7. As mentioned, the weight of whole network is tantamount to 100. Example 1: consider fig. 1 in which node A sends RREQ to node B. At first, node A checks its cache table to see whether there is a route between A and B, or not. If the answer is positive, it starts to send data. If the answer is negative, it sets up RREQ as follow: <A,B,1,7.25,[]> which means: A: source, B: destination, 1: hop count, 7: constitute path weight, 25: request weight, []: intermediate nodes. Each node which receives RREQ will check if it is the destination or not. If it wasn’t: 1. Increase hop count, 2. puts its weight to constitute path weight, 3. Adds its address as an intermediate node. And then broadcasts RREQ packet to the neighbors. In this example node A sends RREQ to X and C, which are legitimate neighbor of A. When X receives the packet, modifies it as: <A,B, 2,(4,25,[X]> and forwards it to its neighbors on the other hand node. C modifies packet as: <A,B,2,(4,25,[C]> and forwards it to its neighbor D. This action will be repeated until B gets two RREQ - <A,B,4,28,25,[C,D,E]> and <A,B,7,25,48,[X,U,V,W, Z,Y> - among the received RREQ, B will be selected which its weight is the same as minimum requested weight by A, or slightly more than that, so the first route will be chosen by B. node B setup RREP packet as <A,B,1,4,25,7, [E,D,C]> which means: A: source, B: destination, 1: back path weight, 4: hop count, 25: request weight, 7: constitute path weight, [E,D,C]: intermediate nodes. The effectiveness of the propose mechanism is evaluated using ns2 network simulator. The simulator's outcome demonstrates that PDR in MAODV rose by 5% up to 8% in presence of two malicious nodes, compared to PDR in AODV routing protocol. The average delay point to point in MAODV is more than AODV, but on the other hand, it is less than SAODV due to not using encryption.}, Keywords = {MANET, Wormhole attacks , AODV, NS2 }, volume = {13}, Number = {4}, pages = {109-120}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.109}, url = {http://jsdp.rcisp.ac.ir/article-1-212-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-212-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {Ghayoomi, Masoo}, title = {A Comparative Study on the Impact of Part-of-Speech Tagging on Parsing for the Persian Language Processing}, abstract ={In this paper, the role of Part-of-Speech (POS) tagging for parsing in automatic processing of the Persian language is studied. To this end, the impact of the quality of POS tagging as well as the impact of the quantity of information available in the POS tags on parsing are studied. To reach the goals, three parsing scenarios are proposed and compared. In the first scenario, the parser assigns the POS tags firstly and then it parses the input sentence. In the second scenario, an external POS tagger is usedto assign the tags, then the sentence is parsed. In the third scenario, the parser uses the gold standard POS tags to parse the input sentence. In this study, various evaluation metrics are used to show the impacts from different points of views. The experimental results show that the quality of the POS tagger and the quantity of the information available in the POS tags have a direct effect on the parsing performance. The high quality of the POS tags causes error reduction in parsing and also it increases parsing performance. Moreover, lack ofmorphological -syntactic information in the POS tags has a high negative impact on parsing performance. This impact is more pronounced than the impact of POS tagger performance. }, Keywords = {processing of the Persian language, part-of-speech tagging, parsing}, volume = {13}, Number = {4}, pages = {121-132}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.121}, url = {http://jsdp.rcisp.ac.ir/article-1-300-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-300-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} } @article{ author = {Jafarian-Moghaddam, Ahmad Reza and Barzinpour, Farnaz and Fathian, Mohamm}, title = {New Clustering Technique using Artificial Immune System and Hierarchical technique}, abstract ={Artificial immune system (AIS) is one of the most meta-heuristic algorithms to solve complex problems. With a large number of data, creating a rapid decision and stable results are the most challenging tasks due to the rapid variation in real world. Clustering technique is a possible solution for overcoming these problems. The goal of clustering analysis is to group similar objects. AIS algorithm can be used in data clustering analysis. Although AIS is able to good display configure of the search space, but determination of clusters of data set directly using the AIS output will be very difficult and costly. Accordingly, in this paper a two-step algorithm is proposed based on AIS algorithm and hierarchical clustering technique. High execution speed and no need to specify the number of clusters are the benefits of the hierarchical clustering technique. But this technique is sensitive to outlier data. So, in the first stage of introduced algorithm the search space and the configuration space are identified using the proposed AIS algorithm, and therefore outlier data are determined. Then in second phase, using hierarchical clustering technique, clusters and their number are determined. Consequently, the first stage of proposed algorithm eliminates the disadvantages of the hierarchical clustering technique, and AIS problems will be resolved in the second stage of the proposed algorithm. In this paper, the proposed algorithm is evaluated and assessed through two metrics that were identified as (i) execution time (ii) Sum of Squared Error (SSE): the average total distance between the center of a cluster with cluster members used to measure the goodness of a clustering structure. Finally, the proposed algorithm has been implemented on a real sample data composed of the earthquake in Iran and has been compared with the similar algorithm titled Improved Ant System-based Clustering algorithm (IASC). IASC is based on Ant Colony System (ACS) as the meta-heuristics clustering algorithm. It is a fast algorithm and is suitable for dynamic environments. Table 1 shows the results of evaluation.   Table 4: Compare the two algorithms Proposed algorithm IASC Alg. 12 18 Execution time (s) 5/3 9/4 SSE   The results showed that the proposed algorithm is able to cover the drawbacks in AIS and hierarchical clustering techniques and on the other hand has high precision and acceptable run speed.}, Keywords = {Clustering Analysis, Artificial immune system (AIS), Hierarchical Clustering.}, volume = {13}, Number = {4}, pages = {133-145}, publisher = {Research Center on Developing Advanced Technologies}, doi = {10.18869/acadpub.jsdp.13.4.133}, url = {http://jsdp.rcisp.ac.ir/article-1-88-en.html}, eprint = {http://jsdp.rcisp.ac.ir/article-1-88-en.pdf}, journal = {Signal and Data Processing}, issn = {2538-4201}, eissn = {2538-421X}, year = {2017} }