Rapid Feature Extraction for Optical Character Recognition

TL;DR

This paper introduces a rapid feature extraction method called Celled Projection for optical character recognition, demonstrating comparable accuracy with existing methods on Bangla handwritten numerals.

Contribution

The paper proposes a new feature extraction technique, Celled Projection, that improves speed while maintaining high recognition accuracy.

Findings

Achieved 94.12% recognition accuracy with Celled Projection

Compared favorably with other feature extraction methods

Validated on Bangla handwritten numerals

Abstract

Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is depends on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled projection.