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- W2040306002 abstract "Finger vein pattern has become one of the most promising biometric identifiers. In this paper, a robust method based on Bag-of-Words (BoW) is developed for finger vein verification. Firstly, some robust and discriminative visual words are learned from local base features such as Local Binary Pattern (LBP), Mean Curvature and Webber Local Descriptor (WLD). We name these visual words as Finger Vein Textons (FVTs). Secondly, each image is mapped into a FVTs matrix. Finally, spatial pyramid matching (SPM) method is applied to maintain spatial layout information by representing each image as pyramid histogram which is performed for matching by histogram intersection function. Experimental results show that the proposed method achieves satisfactory performance both on our database and the open PolyU database. In addition, our method also has strong robustness and high accuracy on the self-built rotation and illumination databases." @default.
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- W2040306002 date "2015-05-20" @default.
- W2040306002 modified "2023-09-26" @default.
- W2040306002 title "Finger Vein Verification with Vein Textons" @default.
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- W2040306002 doi "https://doi.org/10.1142/s0218001415560030" @default.
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