دوره 16، شماره 1 - ( 3-1398 )                   جلد 16 شماره 1 صفحات 111-124 | برگشت به فهرست نسخه ها


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Mostajer Kheirkhah F, Asghari H, Yazdani D. On the use of Textural Features and Neural Networks for Leaf Recognition. JSDP. 2019; 16 (1) :111-124
URL: http://jsdp.rcisp.ac.ir/article-1-792-fa.html
مستاجر خیرخواه فاطمه، اصغری حبیب الله، یزدانی داراب. شناسایی گونه‌های گیاهی با استفاده از تصاویر برگ بر پایه ویژگی‌های بافت و شبکه عصبی. پردازش علائم و داده‌ها. 1398; 16 (1) :111-124

URL: http://jsdp.rcisp.ac.ir/article-1-792-fa.html


پژوهشکده فناوری اطلاعات جهاد دانشگاهی
چکیده:   (303 مشاهده)
برگ گیاهان منبع اطلاعاتی مهمی برای پژوهش و شناسایی گیاهان هستند. استخراج این اطلاعات به‌طورعمومی توسط کارشناسان خبره کشاورزی انجام می­‌گیرد. از آنجا که برگ­ها ویژگی­‌های مناسبی را برای تشخیص انواع گونه‌­های گیاهی در سامانه‌های هوشمند فراهم می‌کنند، لذا استفاده از سامانه‌های هوشمند می‌­تواند به تشخیص خودکار گونه‌­های گیاهی کمک کند. این مقاله روش جدیدی را برای شناسایی برگ‌­های گونه‌­های گیاهی با استفاده از الگوریتم استخراج ویژگی بافت GIST ارائه می‌­دهد که یک روش استخراج ویژگی عمومی برای طبقه‌بندی تصاویر است. این روش دارای دقت خوبی در تعیین شباهت­‌ها بین اشیای یکسان در تصاویر مختلف است. در مرحله طبقه‌­بندی داده‌­ها نیز، از شبکه عصبی Patternnet که برای استخراج الگو مناسب است استفاده می‌شود. برای ارزیابی روش پیشنهادی، الگوریتم حاصل بر روی داده‌­های دو پایگاه داده معتبر که تنوع گیاهی زیادی دارند، اعمال شده است. مقایسه نتایج با الگوریتم‌­های متداول استخراج ویژگی از تصاویر برگ‌­ها نشان می‌­دهد که الگوریتم GIST علاوه‌بر سرعت مناسب، دارای دقت طبقه­‌بندی قابل قبولی به‌ویژه در تصاویر هم‌راستا و حتی تصاویر از نوع شبه‌پویش است.
متن کامل [PDF 3489 kb]   (76 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: مقالات پردازش تصویر
دریافت: ۱۳۹۶/۹/۱۱ | پذیرش: ۱۳۹۷/۱۰/۱۹ | انتشار: ۱۳۹۸/۳/۲۰ | انتشار الکترونیک: ۱۳۹۸/۳/۲۰

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