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| Quality Classification Method for Fingerprint Image Based on Support Vector Machine |
| ZHANG Yu, YIN Yi-Long, LUO Gong-Qing |
| School of Computer Science and Technology, Shandong University, Jinan 250101 |
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Abstract In an automatic fingerprint identification system, estimating the quality of fingerprint image has significant value for segmentation, enhancement and matching processes. Besides, the quality classification of fingerprint image is of paramount significance in the applicability research of fingerprint recognition algorithm. In this paper, a method for quality classification of fingerprint image is proposed based on the support vector machine (SVM). The gradient, Gabor feature, and directional contrast are used as the quality index, and SVM is applied to achieve quality classification of fingerprint image. Meanwhile, synthetic minority over sampling technique (SMOTE) method is employed to reduce the influence of class imbalance problem. Both the theoretical analysis and the experimental results indicate the validity of the proposed method.
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Received: 20 November 2007
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2009, Vol. 22 
