A New Approach using Template Matching for Recognition of Handwritten Odia Text

Abstract

The objective of Handwritten Optical Character Recognition (HOCR) is automatic reading of optically intellect document text materials to translate human-readable characters to machine- readable codes. In Optical Character Recognition, the text lines in a document must be segmented properly before recognition. English Character Recognition (CR) has been extensively studied in the last half century and progressed to a level, sufficient to produce technology driven applications. But same is not the case for Indian languages which are complicated in terms of structure and computations. This is the motivation behind choosing OCR for Odia language. An odia handwritten paragraph is chosen for processing and recognition. The HOCR system is devised to first segment the whole document into text lines, then to words and then to individual characters. These characters are then used to extract the necessary features and recognize those characters and classify them.