Recognition of Handwritten Bangla Basic Characters and Digits using Convex Hull based Feature Set

TL;DR

This paper evaluates a convex hull based feature set for recognizing handwritten Bangla characters and digits, achieving high accuracy especially for numerals, demonstrating its effectiveness in pattern recognition tasks.

Contribution

It introduces and validates a new convex hull based feature set for improved recognition of handwritten Bangla characters and digits.

Findings

Maximum recognition rate of 76.86% for Bangla characters.

Achieved 99.45% success rate for Bangla numerals.

Validated the usefulness of the convex hull based features.

Abstract

In dealing with the problem of recognition of handwritten character patterns of varying shapes and sizes, selection of a proper feature set is important to achieve high recognition performance. The current research aims to evaluate the performance of the convex hull based feature set, i.e. 125 features in all computed over different bays attributes of the convex hull of a pattern, for effective recognition of isolated handwritten Bangla basic characters and digits. On experimentation with a database of 10000 samples, the maximum recognition rate of 76.86% is observed for handwritten Bangla characters. For Bangla numerals the maximum success rate of 99.45%. is achieved on a database of 12000 sample. The current work validates the usefulness of a new kind of feature set for recognition of handwritten Bangla basic characters and numerals.