Comparative analysis of zoning based methods for Gujarati handwritten numeral recognition

Abstract

Gujarati is one of the ancient Indian languages spoken widely by the people of Gujarat state. This paper is concerned with the recognition of handwritten Gujarati numerals. For recognition of Gujarati numerals zoning based Feature extraction method is used. Numeral image is divided in 16×16, 8×8, 4×4 and 2×2 Zones. After feature extraction through the zoning method, Naive Bayes classifier and multilayer feed forward neural network classifier are implemented for the classification of numerals. For the database generation, 14,000 samples of each numeral are used. The overall recognition rates of this method used for recognition of Gujarati numeral using 16×16, 8×8, 4×4 and 2×2 zoning with neural network are 93.03%, 95.92%, 91.89% and 61.78% and with Naive Bayes classifier are 75%, 85.60%, 81% and 53.75% respectively.