Facial Expression Recognition Using Fuzzy Logic

Facial expression recognition is a part and parcel process in human-computer interaction systems (HCI). We present a legitimate procedure for facial expression recognition from Facial features using Mamdani-type fuzzy system. It is Fuzzy Inference System (FIS), which is capable to set up an easy membership relation between different facial expressions. We present a legitimate algorithm for facial region extraction from static image. These extracted facial regions are used for facial feature extraction. Facial features are fed to a Mamdani-type fuzzy rule based system for facial expression recognition. This system recognizes six basic facial expressions namely fear, surprise, joy, sad, disgust and anger. Normal/Neutral is an additional expression and is often categorized as one of the basic facial expressions. So, total output expressions for our system is seven. Another distinct feature of our system is the membership function model of expression output which is based on different psychological studies and surveys. The validation of the model is further supported by the high expression recognition percentage.