doi: 10.4304/jsw.7.10.2294-2300
A Radical Cascade Classifier for Handwritten Chinese Character Recognition
2School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China
Abstract—Radical extraction is the core technique for radical-based Chinese character recognition. In this paper, we proposed a new method of radical extraction – radical cascade classifier. The radical cascade classifier consists of multiple AdaBoost classifiers. It can detect and extract specific radical from characters. To apply cascade classifier to radical extraction, we focus on two main points: feature selection and radical detection. In this paper, we discussed feature selection for the radical cascade classifier and proposed two methods of radical detection. Based on these works, we constructed the radical cascade classifier and conducted experiments on HITPU databases. The experimental results have shown that our approach is efficient.
Index Terms—handwritten Chinese character recognition, radical extraction, cascade classifier
Cite: Enzhi Ni, Changle Zhou, and Minjun Jiang, "A Radical Cascade Classifier for Handwritten Chinese Character Recognition," Journal of Software vol. 7, no. 10, pp. 2294-2300, 2012.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
INSPEC(IET), ULRICH's Periodicals
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