Recognition of Handwritten Bangla Basic Characters and Digits using Convex Hull based Feature Set
This work addresses recognition of handwritten Bangla script, an important domain-specific task, but is incremental as it applies a known feature extraction method to a specific language.
The paper tackled the problem of recognizing handwritten Bangla characters and digits by evaluating a convex hull-based feature set, achieving a maximum recognition rate of 76.86% for characters and 99.45% for numerals on sample databases of 10,000 and 12,000, respectively.
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.