Facial Features for Template Matching Based Face Recognition

TLDR: The results indicate that the elimination of moustache and bear d has not affected the performance of facial featur es detection and the proposed features based template matching has significantly improved the processing time of this method in face recognition research.

Abstract: Problem statement: Template matching had been a conventional method for object detection especially facial features detection at t he early stage of face recognition research. The appearance of moustache and beard had affected the performance of features detection and face recognition system since ages ago. Approach: The proposed algorithm aimed to reduce the effect of beard and moustache for facial features detection a nd introduce facial features based template matching as the classification method. An automated algorithm for face recognition system based on detected facial features, iris and mouth had been d eveloped. First, the face region was located using skin color information. Next, the algorithm compute d the costs for each pair of iris candidates from intensity valleys as references for iris selection. As for mouth detection, color space method was use d to allocate lips region, image processing methods t o eliminate unwanted noises and corner detection technique to refine the exact location of mouth. Fi nally, template matching was used to classify faces based on the extracted features. Results: The proposed method had shown a better features detection rate (iris = 93.06%, mouth = 95.83%) than conventio nal method. Template matching had achieved a recognition rate of 86.11% with acceptable processi ng time (0.36 sec). Conclusion: The results indicate that the elimination of moustache and bear d has not affected the performance of facial featur es detection. The proposed features based template mat ching has significantly improved the processing time of this method in face recognition research.