Analysis of Telugu Palm Leaf Character Recognition Using 3D Feature

Abstract

This paper deals with the recognition of Telugu characters on palm leaf using statistical features. Handwritten character recognition has various applications in post offices, reading aids for blind, library automation and multimedia design. Palm leaf manuscripts contain religious texts and a host of subjects such as art, medicine, music, astrology, law and astronomy. There is an inherent 3D feature for characters on palm leaf called depth. This depth is proportional to the writers stylus pressure applied at each pixel point. This 3D feature of every pixel in an image is used to recognize the palm leaf characters in the present work. The image is divided into zones and the sum of the pixel intensities in each zone is used as a feature vector to recognize the palm leaf characters. As per the literature survey, the recognition accuracy for handwritten characters is less than 60% and also very less amount of work is done for palm leaf character recognition. Using the proposed method the best recognition accuracy obtained for palm leaf characters is 96%.