Smart Technology

B N M Institute of Technology

Face recognition with anti-spoofing


Face recognition has been one of the most interesting and important research field in the past two decades. The reasons come from the need of automatic recognition and surveillance systems, the interest in human visual system on face recognition, and the design of human computer interface, etc.
These researches involve knowledge and researchers from disciplines such as neuroscience, psychology, computer vision, pattern recognition, image processing, and machine learning, etc. Although face liveness detection methods have been proposed to distinguish real and fake faces, they are either time-consuming, costly, or sensitive to noise and illumination and there is still no robust technique against uncontrolled practical cases which may involve different factors such as environment, software and hardware of the system etc. A facial recognition system is a technology capable of recognizing a human face, that works by pinpointing and measuring facial features from a given image. But, this face recognition can be flawed i.e., there is a possibility of face spoofing.
Our project proposes a face recognition system with anti-spoofing features. A ResNet50 neural network is used to train the model for face recognition. For anti-spoofing we use eye blink detection technique for photo attack, reflection of light technique for video attack and remote photo plethysmography technique for mask attack.

Project Team

Manish Kumar G R, Gokul V G, Prathyaksh Narayan, Nikhil M L
Electronics and Communication Engineering


Mrs. Ashwini S Savanth
B N M Institute of Technology
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