A Fusion of Trace Transform and Hamming Distance with Multiresolution Technique for Improved Accuracy Approach Face Based Identification
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Abstract
- This paper proposes a highly robust method for face recognition with variant illumination, scaling, rotation, blur, reflection and difference emotions (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 Hamming distance is employed to measure and determine of similarity between the models and tested images. Finally, our method is evaluated with experiments on the AR and XM2VTS facial databases and compared with other related works (e.g. Eigen face, Enhance-EBGH, Hausdorff ARTMAP and Original 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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