Houjun Huang, Shilei Liu, He Zheng, Liao Ni, Yi Zhang, Wenxin Li
{"title":"DeepVein: Novel finger vein verification methods based on Deep Convolutional Neural Networks","authors":"Houjun Huang, Shilei Liu, He Zheng, Liao Ni, Yi Zhang, Wenxin Li","doi":"10.1109/ISBA.2017.7947683","DOIUrl":null,"url":null,"abstract":"Finger vein verification is using vein patterns to verify a person's identity, which is widely used in various fields. In practice, the method for verification is the most important part of a biometric system, which determines the reliability of the system. In this paper, we propose methods called DeepVein for finger vein verification based on deep convolutional neural networks and conduct experiments to evaluate our methods. The experimental results show that our proposed methods can achieve state-of-the-art performance in accuracy. In addition, we present how the amount of data for training affects the accuracy in the test datasets.","PeriodicalId":436086,"journal":{"name":"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBA.2017.7947683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 39
Abstract
Finger vein verification is using vein patterns to verify a person's identity, which is widely used in various fields. In practice, the method for verification is the most important part of a biometric system, which determines the reliability of the system. In this paper, we propose methods called DeepVein for finger vein verification based on deep convolutional neural networks and conduct experiments to evaluate our methods. The experimental results show that our proposed methods can achieve state-of-the-art performance in accuracy. In addition, we present how the amount of data for training affects the accuracy in the test datasets.