Face Recognition Based on Improved SIFT Algorithm

Abstract—People are usually identified by their faces. Developments in the past few decades have enabled human to automatically do the identification process.Now, face recognition process employs the advanced statistical science and matching methods. Improvements and innovations in face recognition technology during 10 to 15 past years have propelled it to the current status. Due to the wide application of face recognition algorithms in many practical systems, including security control systems, human–computer interaction systems, etc., algorithms with high success rate are highly interested in research areas in recent years.Most of suggested algorithms are about correctly identifying face photos and assigning them to a person in the database. This study focuses on face recognition based on improved SIFT algorithm. Results indicate the superiority of the proposed algorithm over the SIFT.To evaluate the proposed algorithm, it is applied on ORL database and then compared to other face detection algorithms including Gabor, GPCA, GLDA, LBP, GLDP, KGWRCM, and SIFT. The results obtained from various tests show that the proposed algorithm reveals accuracy of 98.75 % and run time of 4.3 seconds which is shorter. The new improved algorithm is more efficient and more accurate than other algorithms. Keywords—face detection; improved SIFT descriptor; KGWRCM; GPCA; GLDA I