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Hand vein recognition Algorithm Based on NMF with Sparsity and Clustering Property Constraints in Feature Mapping Space

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Chinese Journal of Electronics 2019年第6期28卷 1184-1190页

作者： JIA Xu SUN Fuming LI Haojie CAO Yudong School of Electronics and Information Engineering Liaoning University of Technology School of Software Technology Dalian University of Technology

Most of the existed vein features are lack of robustness to light intensity variation, and some algorithms rely on the specified vein data sets, which leads to the limitation of real applications. To solve the problems,we propose a novel vein recognition algorithm based on Nonnegative matrix factorization(NMF) with double regularization terms. The innovations of our algorithm are mainly reflected in the following two aspects: in order to improve feature robustness, a novel feature mapping function is designed to map the initial Histogram of oriented gradient(HOG) feature to a new space; to enhance the recognition performance, an effective NMF model is presented, which not only reduces feature dimension, but also optimizes the feature sparsity and clustering property simultaneously. Experiments show that the proposed algorithm can achieve satisfactory results in terms of False rejection rate(FRR) and False acceptance rate(FAR), which indicates that our algorithm is valuable for other classification problems.

关键词： vein recognition Nonnegative matrix factorization(NMF) Mapping function Feature sparsity

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Direct gray-scale extraction of topographic features for vein recognition

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Science China(Information Sciences) 2010年第10期53卷 2062-2074页

作者： KANG WenXiong 1, LI HuaSong 2 & DENG FeiQi 1 1 College of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China 2 School of Information Engineering, Wuyi University, Jiangmen 529000, China College of Automation Science and Engineering South China University of Technology Guangzhou China School of Information Engineering Wuyi University Jiangmen China

Binarization processing is a key step in most vein pattern recognition, but may create flaws such as leakage of some feature information. In order to overcome this problem, a new approach is explored in this paper which can extract topographic features directly from gray-scale vein images without binarization processing. First, an extreme graph of directional fields (EGDF) is calculated according to neighborhood information of every pixel, and then the intravenous main ridge of the image can be separated step by step from EGDF with the defined constraint template sets. After that, the sub-ridge is extracted from end points of the main ridge in range constraint image with the tracing method of maximal neighboring point. According to contrast experiment the proposed method is better than the traditional processing (performing binarization first and then skeletonization), in that it can overcome the problem that some separate vein lines are extracted incorrectly, and it can avoid extracting two neighboring vein lines as one ridge. As such, the proposed method is an effective way to extract topographic features for vein recognition

关键词： vein recognition feature extraction directional fields

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Hand-Dorsa vein recognition Based on Weighted Pooling of Complementary Features

Hand-Dorsa Vein Recognition Based on Weighted Pooling of Com...

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第31届中国过程控制会议（CPCC2020）

作者： Jun Wang Xiaoling Chen Guoqing Wang Engineering Research Center of Intelligent Control for Underground Space Ministry of Education CUMT School of Information and Control Engineering China University of Mining University of New South Wales

vein recognition is becoming one of the most popular biometric identification methods with the advantage of unique, portable and inherent properties. However, due to unreliable lighting condition and existence of unexpected geometric transformation caused by natural wear or tear and requirement of contact-free, it contributes to great difficulty in designing robust feature representation and classification techniques for vein recognition systems. A novel multiplicative intrinsic component estimation method(MICE) is proposed to remove the instable lighting effect during hand-dorsa vein image acquisition. Besides, a novel bag-of-features(BoF) based framework to hand-dorsa vein recognition through spatial weighted pooling of complementary features is designed to address the problem of unexpected geometric transformation and obtain more discriminative feature representation. Moreover, additional experiment with CUMT-HDVB database and PolyU database illustrates its effectiveness and generalization ability.

关键词： vein recognition Bag of Feature lighting field estimation geometric phrase pooling local contrast estimation

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