دوره 16، شماره 1 - ( 3-1398 )
جلد 16 شماره 1 صفحات 124-111 |
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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
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
پژوهشکده فناوری اطلاعات جهاد دانشگاهی
چکیده: (3918 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.
نوع مطالعه: پژوهشي |
موضوع مقاله:
مقالات پردازش تصویر
دریافت: 1396/9/11 | پذیرش: 1397/10/19 | انتشار: 1398/3/20 | انتشار الکترونیک: 1398/3/20
دریافت: 1396/9/11 | پذیرش: 1397/10/19 | انتشار: 1398/3/20 | انتشار الکترونیک: 1398/3/20
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