Learn More
Face expression recognition is useful for designing new interactive devices offering the possibility of new ways for human to interact with computer systems. In this paper we develop a facial expression recognition system , based on the facial features extracted from facial characteristic points in frontal image sequences. Selected facial feature points(More)
interpersonal communication. Most of the current works on the facial expression recognition attempt to recognize a small set of the prototypic expressions such as happy, surprise, anger, sad, disgust and fear. However the most of the human emotions are communicated by changes in one or two of discrete features. In this paper, we develop a facial expressions(More)
A simple statistical analysis has been used to select the discriminant coefficients of the discrete cosine transform for the face recognition. The proposed procedure is different from the traditional zigzag or zonal masking. It searches for coefficients which have more ability to discriminate different classes better than other coefficients. Also the(More)
In this paper a FIR nonlinear fuzzy filter for image processing, which is most effective in removal of mixed noise, is proposed. In general itpsilas hard to distinguish noise and edges information. This ambiguity leads us to use fuzzy concepts. Fuzzy similarity is used here to suppress noise and preserve edges. Parameters of the membership function are(More)
Mutual information has been used in many clustering algorithms for measuring general dependencies between random data variables, but its difficulties in computing for small size datasets has limited its efficiency for clustering in many applications. A novel clustering method is proposed which estimates mutual information based on information potential(More)