Automatic face recognition in a crowded scene using multi layered clutter filtering and independent component analysis

The objective of this work is the integration and optimization of an automatic face detection and recognition system for crowded scene. Face detection and recognition has many applications in a variety of fields such as authentication, security, video surveillance and human interaction systems. Identifying faces is quite simple for human beings because it comes naturally but it is not so easy to teach a computer to detect faces in an image and recognize them. In this paper new hybrid approach is proposed for face detection and recognition of faces in a given image, which is fully automated process. Face detection is performed by color segmentation, image segmentation and multi layered clutter filtering. The detected faces are given as input to Independent Component Analysis (ICA), which performs face recognition. The proposed approach has achieved high detection and Recognition rate for faces at cluttered background.