  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.
