Automatic face recognition using normalized cross correlation (NCC) function with variable template size
Najat T. Abdulsada, Saleh M. Ali · AIP conference proceedings · 2022
Face detection is one of the most difficult image processing issues. In the many processing stage of face recognition, one of the most important parts is face detection. In the recent years, there has been much progress in face detection. Many face recognition system adopt or develop .We have proposed automatic face detection algorithm of an individual person through of group image by matching the extracted face of the individual person from group image based on Normalized Cross Correlation (NCC) functions and skin detection of variable size of individual person been has face detected . By observing the results, it is clear that Normalized Cross-Correlation (NCC) with skin detection is the best approach for face matching. It gives perfect face matching in the given target image. The maximum cross-correlation coefficient values indicate the perfect matching of extracted face with the target image. The algorithm is implemented in MATLAB. The experimental results show that developed algorithm is robust for similarity measure if the image was not affected by pose-variation.