Gujarati Handwritten Numeral Optical Character through Neural Network and Skeletonization

Abstract

This paper deals with an optical character recognition (OCR) system for handwritten Gujarati numbers. One may find so much of work for Indian languages like Hindi, Kannada, Tamil, Bangala, Malayalam, Gurumukhi etc, but Gujarati is a language for which hardly any work is traceable especially for handwritten characters. The features of Gujarati digits are abstracted by four different profiles of digits. Skeletonization and binarization are also done for preprocessing of handwritten numerals before their classification. This work has achieved approximately 80,5% of success rate for Gujarati handwritten digit identification.