Zone based handwritten Kannada character recognition using crack code and SVM

Efficient methods have been proposed in the literature for recognition of printed characters of Indian scripts. However, much less attention has been received for handwritten characters of Indian scripts with only a few work available in the literature. In this paper, a novel zone based method has been presented for recognition of handwritten characters written in Kannada language, a major South Indian language. The normalized character image is divided into 64 zones each of size 8x8 pixels. For each zone, from left to right and from top to bottom, the crack code, representing the line between the object pixel and the background (the crack), is generated by traversing it in anticlockwise direction. A feature vector of size 512 is obtained for each character. A multi-class SVM is used for the classification purpose. Experiments are performed on handwritten Kannada character images consisting of 24500 images with 500 samples of each character. Five-fold cross validation is used for result computation that yielded 87.24% recognition accuracy.