نظام التعرف على الحروف العربية المعزولة في وضع عدم الاتصال بناءً على SVM -أريد

نوع النشر: مقال علمي
المؤلفون بالعربي: علياء كريم عبد الحسن, مصطفى سلام كاظم
المؤلفون بالإنجليزي: Dr. Alia Karim Abdul Hassan, Mustafa Salam Kadhm
الملخص العربي: This paper proposed a new architecture for Offline Isolated Arabic Handwriting Character Recognition System Based on SVM (OIAHCR). An Arabic handwriting dataset also proposed for training and testing the proposed system. Although half of the dataset used for training the SVM and the second half used for testing, the system achieved high performance with less training data. Besides, the system achieved best recognition accuracy 99.64% based on several feature extraction methods and SVM classifier. Experimental results show that the linear kernel of SVM is convergent and more accurate for recognition than other SVM kernels.
تاريخ النشر: 01/05/2019
الناشر: The International Arab Journal of Information Technology
رقم المجلد: 15
رقم العدد: 3
الصفحات: 467-472
رابط خارجي: http://iajit.org/PDF/May%202019,%20No.%203/11448.pdf
الكلمات المفتاحية: Arabic character, pre-processing, feature extraction, classification.