收稿日期: 2016-08-04
修回日期: 2016-08-17
网络出版日期: 2016-09-30
基金资助
国家自然科学基金（No.61672294，No.61173141，No.U1536206，No.61232016，No.U1405254，No.61373133，No.61373132，No.61502242，No.61572258）；江苏高校优势学科建设工程PAPD基金；大气环境与装备技术协同创新中心（CICAEET）基金资助
Fingerprint Liveness Detection Based on Weber Binarized Perception Features
Received date: 2016-08-04
Revised date: 2016-08-17
Online published: 2016-09-30
吕锐, 夏志华, 陈先意, 孙星明 . 基于韦伯二值感知特征的指纹活性检测[J]. 应用科学学报, 2016 , 34(5) : 616 -624 . DOI: 10.3969/j.issn.0255-8297.2016.05.014
Based on Weber binarized perception features (WBPF), we propose a fingerprint liveness detection method. It consists of two components: local binary differential excitation (LBDE) for extracting perception features by Weber's law, local binary gradient orientation (LBGO) for extracting gradient based orientation features. The features are used to train SVM classifiers on two publicly available databases used in the Fingerprint Liveness Detection Competition 2011 and 2013. Experimental results show that the proposed method outperforms the state-of-the-art liveness detection techniques.
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