A new tree-like fuzzy binary support vector machine for optical character recognition

Guo-yun Zhang; Jing Zhang

doi:10.1117/12.572086

8 February 2005 A new tree-like fuzzy binary support vector machine for optical character recognition

Guo-yun Zhang, Jing Zhang

Proceedings Volume 5637, Electronic Imaging and Multimedia Technology IV; (2005) https://doi.org/10.1117/12.572086
Event: Photonics Asia, 2004, Beijing, China

Abstract

This paper proposes a new tree-like fuzzy binary support vector machines multi-class classifier (FBSVM) for the optical character recognition task. We construct this tree-like classifier by fusing of fuzzy clustering technique and support vector machine (SVM). In k-class task, the new classifier contains k-1 SVM sub-classifiers, but the "one-against-one" method which is usually used contains k(k-1)/2 sub-classifiers. This method also overcomes the drawback such as unclassifiable region that the "one-against-one" method has, and has a good classification performance. Furthermore, it needs less memory. By applying the new classifier to the real mail zipcode digits recognition task, the experimental results indicate that the FBSVM has a better recognition performance.

Citation Download Citation

Guo-yun Zhang and Jing Zhang "A new tree-like fuzzy binary support vector machine for optical character recognition", Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); https://doi.org/10.1117/12.572086

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