The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This mod...
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The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This mod...
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ISBN:
(纸本)9781424421749
The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors, subjective factors and variable factors. We adopt different strategies to compute the corresponding three level qualities: database level quality, class level quality and image level quality. The database level quality is estimated by experience. Then, we compute the mean value of variable number of normalized genuine scores, the quantiles of which are used to determine the class level quality. On the image level quality evaluation, a novel concept of subset frequency is proposed.
It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In...
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ISBN:
(纸本)0769521282
It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In this paper, an iris image synthesis method based on principal component analysis (PCA) and super-resolution is proposed. The iris recognition algorithm based on PCA is first introduced and then, iris image synthesis method is presented. The synthesis method first constructs coarse iris images with the given coefficients. Then, synthesized iris images are enhanced using super-resolution. Through controlling the coefficients, we can create many iris images with specified classes. Extensive experiments show that the synthesized iris images have satisfactory cluster and the synthesized iris databases can be very large.
Face recognition is a focused issue in patternrecognition over the past decades. In this paper, we have proposed a new scheme for face recognition using 3D information. In this scheme, the scattered 3D point cloud is...
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ISBN:
(纸本)0769521223
Face recognition is a focused issue in patternrecognition over the past decades. In this paper, we have proposed a new scheme for face recognition using 3D information. In this scheme, the scattered 3D point cloud is first represented with a regular mesh using hierarchical mesh fitting. Then the local shape variation information is extracted to characterize the individual together with the global geometric features. Experimental results on 3D/spl ***/RMA, a likely largest 3D face database available currently, demonstrate that the local shape variation information is very important to improve the recognition accuracy and that the proposed algorithm has promising performance with a low computational cost.
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