Extended right-angle difference ternary co-relation pattern: A new feature descriptor for face anti-spoofing

Abstract

Presently, in many applications face recognition is commonly used as an authentication security system. However, an intruder can spoof the face recognition system by using genuine user photos or video to gain access. Therefore, there is a need for a superior technique for face anti-spoofing to handle all kinds of spoofing attacks in any environment. This paper presents a novel descriptor called extended right-angle difference ternary co-relation pattern (ERDTCP) for face anti-spoofing. The ERDTCP is calculated based on the division of a given image into 4 blocks at an angle of 0°, 90°, 180° and 270° from the center pixel. The effectiveness of the proposed method is evaluated on three publically available databases using KNN and SVM classifiers. Experiments were conducted using SOTA approaches and the proposed method using ERDTCP and the results were compared. The proposed face anti-spoofing approach performs better than SOTA approaches.