期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：9
页码：19226
DOI：10.15680/IJIRSET.2017.0609061
出版社：S&S Publications
摘要：Accurate biometric system for authentication is the need of the hour in today’s scenario. In face spoofingattack a person tries to pretend to be a valid user by using photo or video of an authorized person and gets illegitimateaccess. Hence it is essential to develop a robust and authentic face spoof detection system in order to protect theprivacy about the person. Centre of attraction of this paper is face spoofing detection system using Image DistortionAnalysis (IDA). Analysis of distortion of an image to identify spoof attack is the principle consideration of theproposed system. This paper extracts four different IDA features-Specular Reflection, Blurriness, Chromatic Momentand Colour Diversity which are concatenated together to form IDA feature vector. IDA feature vector is further usedfor face spoof detection using Support Vector Machine (SVM) and Artificial Neural Network (ANN). This paperhighlights the performance of accuracy of SVM and ANN using in term of True Acceptance Rate (TAR) and TrueRecognition Rate (TRR). The performance of classifier was tested on the data-set of public-domain face spoofdatabases MSU MFSD face images. It was observed that the TAR vs TRR for SVM is 94.4% while that for ANN is88.9%. The performance of accuracy indicated that the spoof detection based on IDA using SVM is more secured thanANN.
