per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
3
12
article
A New Authentication System Based on Wavelet and Contourlet Transforms for Low Quality Palmprint Images
saeed_ayat@yahoo.com
1
mrkh83@gmail.com
2
This paper proposed an authentication system based on low quality palmprint. For implementation of this system, first the features is extracted by using Contourlet and wavelet transforms. In the second phase, some of the features are selected by using Across Group Variance (AGV) filter. In the last phase by using a classification method, the authentication is completed. For classification we evaluated three different methods, Support Vector Machine (SVM), Revised Nearest Neighbor (RNN), and Boosted Direct Linear Discriminant Analysis (BDLD). The experiment is performed on the famous PolyU Palmprint database. The results shows that by combination of the proposed system and BDLD classifier has better performance in comparison to other methods and the same database.
http://jsdp.rcisp.ac.ir/article-1-718-en.pdf
Palmprint
Authentication
Biometric
Contourlet Transform
Wavelet Transform
AGV
per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
13
22
article
as
sheikhzadegan@rcdat.ir
1
a_vizand@yahoo.com
2
amrghdri@ihu.ac.ir
3
as
http://jsdp.rcisp.ac.ir/article-1-721-en.pdf
as
per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
23
36
article
Reducing the Periodic Noise Effects in Digital Image by an Adaptive Median Filter in the Frequency Domain
P_moallem@eng.ui.ac.ir
1
monadjemi@eng.ui.ac.ir
2
majidbehnam20@gmail.com
3
Periodic noises are repetitive patterns on digital images and decreased the visual quality of images. The various methods for reducing the effects of the periodic noise in digital images are firstly investigated. Then an intelligent median filter in the frequency domain with an acceptable computational cost is proposed. In the proposed method, the regions of noise frequencies are determined by analyzing intelligently the spectral of noisy image. Then only for the destroyed frequencies by periodic noise, a median filter with proper size in the frequency domain is applied and the spectrum of the image with reduced periodic noise is computed. The compared methods including the proposed method, the mean and the median filtering techniques, all in frequency domain are implemented not only under MATLAB environment, but also by C programming under OpenCV library. The results in different conditions show that the proposed filter shows higher performances, visually and statistically, and also in needs very lower computational cost.
http://jsdp.rcisp.ac.ir/article-1-717-en.pdf
Periodic Noise
Filtering in Frequency Domain
Adaptive Median Filter
per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
37
48
article
Improvement of Telephone Keyword Spotting Performance Using Linear Programming-Based Score Normalization
1
2
3
4
Conventional word spotting systems determine hypothesized keywords and their confidence score using a speech recognizer. Acceptance or rejection of these keywords is intended based on comparison of their scores with a specific threshold. It has been proved that confidence score prepared by recognizer is highly dependent on sub-word structure of each keyword. So comparing assigned scores to keywords without considering their sub-word units could causes degradation in overall performance. In this paper a novel method for confidence score normalization is proposed which is based on sub-word units of each keyword and linear programming algorithm. In proposed method, a keyword-dependent correction term is added to the score of the keyword to maximize separation of confidence score histograms of true and false occurrences. Our results show a 2% improvement in FOM compared to baseline system. Also, choosing an appropriate feature vector has been discussed in this paper.
http://jsdp.rcisp.ac.ir/article-1-716-en.pdf
Keyword spotting
Hidden Markov Model
Confidence score
Linear programming
Score normalization.
per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
59
68
article
Designing a Currency Recognition System Based on Neural Networks Using Texture and Color of Images
mehregan_m@hotmail.com
1
Habib Ahaki
habib.ah57@gmail.com
2
Babak Nasersharif
b.nasersharif@gmail.com
3
Since money exchange is important in our daily life, many types of equipments such as Vending Machines, Currency Sorters, Automatic Teller Machines (ATM) and Currency Recognition systems for blind people have been made. More advanced devices with more capabilities are being made each day. As a result, efficient, fast and reliable currency recognition methods are required. Most currency recognition methods only use one attribute of currency images, such as major color, Ultra Violet spectrum or texture that are extracted from currency images. In this paper, we introduce a method for currency recognition that combines texture and color data together and applies them to a neural network. The best result from the other existing methods is at most 85 percent but our method shows 10 percent improvement compared to existing solutions.
http://jsdp.rcisp.ac.ir/article-1-720-en.pdf
Currency Recognition
Image Processing
Neural Network
Digital Filter
per
Research Center on Developing Advanced Technologies
Signal and Data Processing
2538-4201
2538-421X
2011-03
7
2
69
84
article
Design and Evaluation of a Persian TTS system using prosodically-sensitive concatenative units
va_sadeghi2000@yahoo.com
1
This paper describes the design and evaluation of prosodically-sensitive concatenative units for a Persian text-to-speech (TTS) synthesis system. Thesyllables used are prosodically conditioned in the sense that a single conventional syllable is stored as different versions taken directly from the different prosodic domains of the prosodically labeled, read sentences. The three levels of the Persian prosodic hierarchy were observed in the syllable selection process, thereby selecting three different versions of each syllable from the prosodic domains of the intonational phrase (IP), accentual phrase (AP) and prosodic word (PW). A listening experiment designed to evaluate the quality of the syllable database showed that listeners preferred stimuli composed of prosodically appropriate diphones. We interpret this as supporting the view that segments carry prosodic domain information.
http://jsdp.rcisp.ac.ir/article-1-715-en.pdf
concatenation-prosodically sensitive units- synthesis