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Proceedings Paper

Face recognition by Hopfield neural network and no-balance binary tree support vector machine
Author(s): Ke Wang; Haitao Jia
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Paper Abstract

In the biometric recognition, face recognition is the most natural, direct method. Research on face recognition has a high theoretical significance and practical value. In this paper, firstly we use the Gabor filter to extract face image features, and then denote to further dimensionality reduction by Hopfield Neural Network. At last, for face classification, a new method based on support vector machine- No-balance Binary Tree Support Vector Machine (NBBTSVM) is proposed to decide a label in this face recognition task. SVM has excellent performance to solve binary classification but for multi-classification, it's an ongoing research. According to our experiment results, NBBTSVM could do a good performance.

Paper Details

Date Published: 26 February 2010
PDF: 8 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75462K (26 February 2010); doi: 10.1117/12.855076
Show Author Affiliations
Ke Wang, Univ. of Electronic Science and Technology of China (China)
Haitao Jia, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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