عنوان المقالة:التعرف على الكلمات المكتوبة بخط اليد باستخدام SVM Handwriting Word Recognition Based on SVM Classifier
أ.م.د مصطفى سلام كاظم | Mustafa Salam Kadhm | 15708
نوع النشر
مقال علمي
المؤلفون بالعربي
علياء كريم عبد الحسن, مصطفى سلام كاظم
المؤلفون بالإنجليزي
Mustafa S. Kadhm, Asst. Prof. Dr. Alia Karim Abdul Hassan
الملخص العربي
this paper proposed a new architecture for handwriting word recognition system Based on Support Vector Machine SVM Classifier. The proposed work depends on the handwriting word level, and it does not need for character segmentation stage. An Arabic handwriting dataset AHDB, dataset used for train and test the proposed system. Besides, the system achieved the best recognition accuracy 96.317% based on several feature extraction methods and SVM classifier. Experimental results show that the polynomial kernel of SVM is convergent and more accurate for recognition than other SVM kernels
تاريخ النشر
06/11/2015
الناشر
International Journal of Advanced Computer Science & Applications
رقم المجلد
6
رقم العدد
11
رابط DOI
10.14569/IJACSA.2015.061109
الصفحات
64-68
رابط خارجي
https://thesai.org/Downloads/Volume6No11/Paper_9-Handwriting_Word_Recognition_Based_on_SVM_Classifier.pdf
الكلمات المفتاحية
Arabic Text; Preprocessing; Feature Extraction; SVM
رجوع