An Efficient Human Face Recognition Approach: Combination of Eigenface and k-Means Clustering methods

Facial expressions convey non verbal cues, which play an important role in interpersonal relations. Automatic recognition of human face based on facial expression can be important component of natural human-machine interface. It may also be used in behavioral science. Although human can recognize the face practically without any effort, but reliable face recognition by machine is a challenge. This book presents a new approach for recognizing the face of a person considering the expression of the same human face at different instant of time. This methodology is developed combining Eigenface method for feature extraction and k-Means clustering for identification of the human face. In experimental purpose, AT&T face database is used which contains a set of 40 people with 10 images with different facial expressions at the different illumination. Experimental results demonstrate the efficacy of the approach. This book is written such a manner that it will help researchers to work on the area of image processing and pattern recognition. It also helps graduate students to know the background and basic theories of different face recognition methods.