Performance analysis of canny edge detection for illumination invariant Facial Expression recognition

Face perception is a very important component of human cognition. We can judge the person´s mood and mental status through his/her expressions. In other words, the most expressive way human display emotion is through facial expressions. And hence facial expression recognition has become an active research area in the field of human computer interaction. The work in this paper concentrates on images having different illuminations and analyzes the performance of canny edge detection method with two classifiers, Euclidian distance and neural network. The results are tested on JAFFE (Japanese Female Facial Expression) database, available in public domain and IFE (Indian Facial Expression) database which is self created.