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 | 15679
- 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