A Complete Machine-Printed Gurmukhi OCR System

Abstract

Recognition of Indian language scripts is a challenging problem and work towards the development of a complete OCR system for Indian language scripts is still in its infancy. Complete OCR systems have recently been developed for Devanagari and Bangla scripts. However, research in the field of recognition of Gurmukhi script faces major problems mainly due to the unique characteristics of the script such as connectivity of characters on a headline, characters pointing in both horizontal and vertical directions, two or more characters in a word having intersecting minimum bounding rectangles along horizontal direction, existence of a large set of visually similar character pairs, multi-component characters, touching and broken characters, and horizontally overlapping text segments. This chapter addresses the problems in the various stages of the development of a complete OCR system for Gurmukhi script and discusses potential solutions. A multi-font Gurmukhi OCR for printed text with an accuracy rate exceeding 96% at the character level is presented. A combination of local and global structural features is used for the feature extraction process, aimed at capturing the geometrical and topological features of the characters. For classification, we have implemented a multi-stage classification scheme in which the binary tree and k-nearest neighbor classifiers have been used in a hierarchical fashion.