Recognition Method for Handwritten Digits Based on Improved Chain Code Histogram Feature

DOI

10.2991/icmt-13.2013.53How to use a DOI?

Keywords

Chain code histogram,·Differential chain code·Direction turning point·Handwritten digit recognition·Support vector machine

Abstract

The chain code histogram feature is a simple and effective feature extraction technology. This paper proposes improvements based on Chain Code Histogram (CCH) and its first differential characteristics. According to the first Differential Chain Code Histogram (DCCH), the turning points in the direction are extracted and the judging method of Direction Turning Point (DTP) is given. We combine CCH and DTP into a new feature, then handwritten digits of MNIST database are recognized and classified by Support Vector Machine (SVM) classifier. The experimental results proved that the recognition rate of the improved method is not only higher than CCH and first differential CCH, but also closely to the recognition rate of their combination. Obviously, the new combination reduces the feature dimension, improves the speed of training and recognition.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - You Qian
AU  - Wang Xichang
AU  - Zhang Huaying
AU  - Sun Zhen
AU  - Liu Jiang
PY  - 2013/11
DA  - 2013/11
TI  - Recognition Method for Handwritten Digits Based on Improved Chain Code Histogram Feature
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 431
EP  - 438
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.53
DO  - 10.2991/icmt-13.2013.53
ID  - Qian2013/11
ER  -