Improved zoning and cropping techniques facilitating segmentation

Abstract

In the advent of digital computers and era where work force is shifted to be inclined on robotic process, Optical Character Recognition (OCR) has immense potentials to ease some these processes. Segmentation is one of the pre-processing phases- the pivotal essence of the process where lingual scripts and their characteristics vary to a much larger extent. This paper focuses on techniques which facilitates segmentation in Devanagari script (Hindi) for offline handwritten words i.e. Headline detection in handwritten word images of Hindi for extracting upper and middle zone characters and cropping. Experiments are performed on the handwritten legal amount words ICDAR database [1] on 106 words by 80 writers and on Self created touching character database on 106 words by 15 writers. The proposed zoning technique i.e. CPT (Continuous pixel technique) and cropping techniques is implemented on 10070 and 530 legal amount words with 98.89% accuracy and 80.94% respectively.