An application of SVM in character recognition with chain code

Artificial intelligence, pattern recognition and computer vision has a significant importance in the field of electronics and image processing. Optical character recognition (OCR) is one of the main aspects of pattern recognition and has evolved greatly since its beginning. OCR is a system which recognized the readable characters from optical data and converts it into digital form. Various methodologies have been developed for this purpose using different approaches. In this paper, general architecture of modern OCR system with details of each module is discussed. We applied Moore neighborhood tracing for extracting boundary of characters and then chain rule for feature extraction. In the classification stage for character recognition, SVM is trained and is applied on suitable example.