Facial expression recognition using fast walidlet hybrid transform

Abstract EN

Automatic analysis of facial expressions is rapidly becoming an area of intense interest incomputer vision and artificial intelligence research communities.

In this paper an approach is presented forfacial expression recognition of the six basic prototype expressions (i.

e.

, joy, surprise, anger, sadness, fear, and disgust) based on Facial Action Coding System (FACS).

The approach is attempting to utilize acombination of different transforms (Walid let hybrid transform); they consist of Fast Fourier Transform; Radon transform and Multiwavelet transform for the feature extraction.

Korhonen Self Organizing FeatureMap (SOFM) then used for patterns clustering based on the features obtained from the hybrid transformabove.

The result shows that the method has very good accuracy in facial expression recognition.

However, the proposed method has many promising features that make it interesting.

The approach provides a newmethod of feature extraction in which overcome the problem of the illumination, faces that varies from oneindividual to another quite considerably due to different age, ethnicity, gender and cosmetic also it does notrequire a precise normalization and lighting equalization.

An average clustering accuracy of 94.8% isachieved for six basic expressions, where different databases had been used for the test of the method