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Volume: 29 | Article ID: art00016
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Face Spoofing Detection Based on Local Binary Descriptors
  DOI :  10.2352/ISSN.2470-1173.2017.13.IPAS-208  Published OnlineJanuary 2017
Abstract

Due to the popularity of the internet, mobile devices have become the main way for delivering messages and online transactions in our daily life. However, facilitate of online transactions will easily derivate security issues. Because of its unique and irreplaceable nature, biometric technology has been widely used in the areas of identification. Among biometrics, face recognition technology for online payments is recently developed. Nowadays, most people still worried about the spoofing of face recognition technology. Under this situations, there are many research results focusing on the important and urgent subjects. Local binary pattern in images is very useful for image processing and computer vision applications like face recognition. Based on the local pattern analysis, we developed a hierarchical analysis algorithm for extracting texture feature such that they not only give a satisfying representation of a face image, but also make the spoofing detection process efficiently. Experimental results show that the proposed method can be applied to a real system for face recognitions.

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  Cite this article 

Yao-Hong Tsai, Yu-Jung Lin, "Face Spoofing Detection Based on Local Binary Descriptorsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems XV,  2017,  pp 105 - 108,  https://doi.org/10.2352/ISSN.2470-1173.2017.13.IPAS-208

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Copyright © Society for Imaging Science and Technology 2017
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