Rapid Feature Extraction for Optical Character Recognition
This work addresses feature extraction for character recognition, particularly for Bangla script, but appears incremental as it builds on existing methods with comparable results.
The paper tackled the problem of feature extraction for optical character recognition by proposing a rapid method called Celled Projection (CP), which achieved a recognition accuracy of 94.12% on Bangla handwritten numerals.
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.