Rerkchai Fooprateepsiri and Werasak Kurutach
Biometric, Face Recognition, Multi-resolution Trace Transform, Fuzzy ART
Face recognition research still face challenge in some specific domains such as pose, illumination and Expression (PIE). This paper proposes a highly robust method for face recognition with variant pose, illumination, scaling, rotation, blur, reflection and difference expression (smiling, angry and screaming). Techniques introduced in this work are composed of two parts. The first one is the detection of facial features by using the concept of multi-resolution Trace transform. Then, in the second part, the supervised fuzzy ART is employed to measure and determine of similarity between the models and tested images. Finally, our method is evaluated with experiments on the XM2VTS and FERET face databases and compared with other related works (e.g. Eigen face, Enhance-EBGH, Hausdorff ARTMAP and Trace-Hamming). The extensive experimental results show that the average of accuracy rate of face recognition with variant pose, illumination, scaling, rotation, blur, reflection and difference expression is very high and it was found that our proposed method performed better than the other related works in all cases.
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