Development of a Feature Extraction Technique for Online Character Recognition System

Abstract

Character recognition has been a popular research area for many years because of its various application potentials. Some of its application areas are postal automation, bank cheque processing, automatic data entry, signature verification and so on. Nevertheless, recognition of handwritten characters is a problem that is currently gathering a lot of attention. It has become a difficult problem because of the high variability and ambiguity in the character shapes written by individuals. A lot of researchers have proposed many approaches to solve this complex problem but none has been able to solve the problem completely in all settings. Some of the problems encountered by researchers include selection of efficient feature extraction method, long network training time, long recognition time and low recognition accuracy. This paper developed a feature extraction technique for online character recognition system using hybrid of geometrical and statistical features. Thus, through the integration of geometrical and statistical features, insights were gained into new character properties, since these types of features were considered to be complementary.

Keywords: Character recognition, Feature extraction, Geometrical Feature, Statistical Feature, Character.