A face recognition system using fuzzy logic and artificial neural network
Kyoung-Man Lim, Young-Chul Sim, Kyung-Whan Oh · 2003
The authors have developed a method to extract a feature vector that is very important to recognizing facial images. The eye blinking method was used to get the location of the eyes roughly. Then a feature vector was obtained using locations and distances between feature points, that is the eyes, the nose, the mouth and the outline of the face. To make the feature vector invariant to the size of the facial image, it was normalized. Fuzzy linguistic variables were used instead of real numbers to represent the approximate distance between feature points. These fuzzified feature vectors were learned by an artificial neural network and used to recognize a facial image in the recognition phase. The face recognizer could recognize all learned persons correctly in spite of variations.>