Chinese Numeral Recognition Using Gabor and SVM

Handwritten character recognition has received extensive attention in academic and production fields. The recognition system can be either on-line or off-line. Off-line handwriting recognition is the subfield of Optical Character Recognition . In this paper, We introduce the fundamental principles of Chinese handwritten numerals, including digital image preprocessing, segmentation, features extraction and pattern recognition. The numerals are recognized by SVM classifiers, and their results are combined to form final results. A Novel approach is proposed for recognizing Handwritten Chinese numerals using direction feature extraction approach combined with Gabor and SVM It has been proved that the performance of the system is satisfactory, when both gabor and SVM are used rather than SVM alone. Experimental result shows that our proposed approach are efficient and effective with a recognition rate and accuracy of 95.44%.