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Face-based biometric authentication systems are being widely used nowadays and this use is on the rise. Because of its conveniences over the traditional access schemes, it is prevailing authentication systems. But this system has the drawback of being vulnerable to spoofing attacks. Attackers can bypass this system by presenting a printed photo or a photo in an electronic display in front of the system. In this work, we have tried to detect facial spoof. We have designed our model based on the fact that the recapturing of an image degrades the image quality. To assess the quality, we have extracted features from the images and created a feature vector. Both full reference and no reference methods have been used as an evaluator of image quality. A support vector machine (SVM) has been used for classifying the images using the feature vectors.

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Correspondence to Sharad Hasan .

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Das, T.R., Hasan, S., Sarwar, S.M., Das, J.K., Rahman, M.A. (2021). Facial Spoof Detection Using Support Vector Machine. In: Kaiser, M.S., Bandyopadhyay, A., Mahmud, M., Ray, K. (eds) Proceedings of International Conference on Trends in Computational and Cognitive Engineering. Advances in Intelligent Systems and Computing, vol 1309. Springer, Singapore.

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