Project Title: Texture and Color Quality Analysis for Face Spoofing Detection using ML and DL Techniques

Team Members

Dr. G. Padmavathi, Dean - PSCS, Professor, Department of Computer Science

Mrs. S. Karthika, Assistant Professor, Department of Information Technology

Ms. A. Roshni, Research Assistant, Centre for Cyber Intelligence, DST - CURIE - AI

Ms. G. Indhumathi, M.Sc Information Technology

Project Summary

Existing face bio - metric systems are susceptible to spoofing attacks. A spoofing attack happens when someone attempts to impersonate someone by falsifying information and gaining unauthorized access. We suggested approaching the Spoofing identification from the standpoint of texture classification, engendered by contrast enhancement, characteristics of printing artifacts, and variations in light reflection In fact, face prints frequently have able to print top notch faults that can be discovered using surface as well as local texture. The human body of studies on pro software-based face attacker uses classification methods has focused on gray – level documentation in face images, disregarding a same Chromo component, that can be very important in differentiating between fake and honest faces This article explains a novel as well as appealing texture analysis analysis technique for identifying face spoofing. We use complement low in fat and high explanations from different color spaces to manipulate the joint image feature extraction from the chrominance and luminance channels.