Automatic Recognition of Printed Oriya Script

This paper deals with an Optical Character Recognition (OCR) system for printed Oriya script. The development of OCR for this script is difficult because a large number of character shapes in the script have to be recognized. In the proposed system, the document image is first captured using a flat-bed scanner and then passed through different preprocessing modules like skew correction, line segmentation, zone detection, word and character segmentation etc. These modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of water overflow from a reservoir. The feature detection methods are simple and robust, and do not require preprocessing steps like thinning and pruning. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.