Novel Method for Face Recognition using Laplacian of Gaussian Mask with Local Contour Pattern

• Published in: KSII transactions on Internet and information systems 2016-11, Vol.10 (11), p.5605-5623
• Main Authors: Jeon, Tae-jun, Jang, Kyeong-uk, Lee, Seung-ho
• Format: Article
• Language: Korean
• Subjects: Computer Vision Systems; Face Recognition; Local Contour Pattern (LCP); Nearest Neighbor Classifier; Pattern Recognition
• ISSN: 1976-7277; 1976-7277

We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual`s recognition capability, and outperforms the existing methods.