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14 August 2019 Novel algorithm for finger vein recognition based on inception-resnet module
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791D (2019) https://doi.org/10.1117/12.2539624
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
Abstract
The finger vein feature extraction algorithm based on global or local features is sensitive to rotation, translation and scaling. Convolutional neural networks have higher robustness, but fewer finger vein samples are prone to over-fitting. Therefore, this paper designs a network architecture FingerveinNet for finger vein recognition. Firstly, based the Inception-resnet[1] module, the design of the finger vein network architecture is used to extract the multi-scale finger vein features while slowing down the gradient disappearance problem without increasing the parameters. Secondly, the center-loss is used as the loss function to optimize the network model and improve. The discriminability of feature vectors for better detail discrimination. Experiments on three international finger vein databases FV-TJ, FV-USM and PolyU show that the proposed method is robust to rotation and translation, and the effectiveness of the proposed method is verified.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xian Wang, Huabin Wang, Ying He, Yijun Ding, and Liang Tao "Novel algorithm for finger vein recognition based on inception-resnet module", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791D (14 August 2019); https://doi.org/10.1117/12.2539624
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