Face detection cum recognition system using novel techniques for human authentication

Face biometric plays a significant role in human authentication system; today in several sectors to recognise a person face biometrics are used. Still, in accuracy point of view, there is a lag in the perfect recognition system. In this work, ideas are proposed to develop novel face recognition, face detection, and face detection cum recognition system. A novel Gray-averaging technique is combined with blooming feature extraction techniques called location averaging technique and max-min comparison technique for face recognition and face detection. An existing frequency domain process DCT is also joined with this system. In this system spatial domain and frequency domain techniques are united, hence it acts as a bridge between these two techniques. The face detection cum recognition system is validated using parameters like image size, runtime, and accuracy with few face databases. This novel system is examined through five standard face databases and 300 real-life face images.