An Adaptive Approach for Facial Expression Recognition System
Facial expressions are non-verbal signs that play important role to provide complete meaning in human communication. While humans can easily comprehend the facial expressions, it is not valid for the computers. Therefore, the researchers are still working on developing reliable facial expression recognition systems. In this paper, the analysis of six different human facial expressions (anger, disgust, fear, happiness, sadness and surprise) is examined from human facial images. For this purpose, the features for every facial expression are extracted using the Gabor Lapla-cian of Gaussians (LoG) filter. Image dimension has been reduced to by Principal Component Analysis method and the classification process is made by Euclidean distance calculation.