  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 an important component of natural human-machine interface. It
may also be used in behavioural science. Although human can recognize the face
practically without any effort, but reliable face recognition by machine is a
challenge. This paper presents a new approach for recognizing the face of a
person considering the expressions of the same human face at different
instances of time. This methodology is developed combining Eigenface method for
feature extraction and modified k-Means clustering for identification of the
human face. This method endowed the face recognition without using the
conventional distance measure classifiers. Simulation results show that
proposed face recognition using perception of k-Means clustering is useful for
face images with different facial expressions.
