Face recognition by Hopfield neural network and no-balance binary tree support vector machine

Ke Wang; Haitao Jia

doi:10.1117/12.855076

26 February 2010 Face recognition by Hopfield neural network and no-balance binary tree support vector machine

Ke Wang, Haitao Jia

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75462K (2010) https://doi.org/10.1117/12.855076
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

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.

Citation Download Citation

Ke Wang and Haitao Jia "Face recognition by Hopfield neural network and no-balance binary tree support vector machine", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75462K (26 February 2010); https://doi.org/10.1117/12.855076

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