Real-Time Face Identification for KIOSK Application

• Main Authors: Wei-Jie Liao, 廖威傑
• Other Authors: Daw-Tung Lin
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/21704510127059624958

碩士 === 國立臺北大學 === 資通科技產業碩士專班 === 102 === Face identification for security systems has become an important research subject. This thesis proposes a face identification system for application in area access control systems. Support vector machine (SVM) was employed to conduct face identification based on a data clustering method. Initially, the face was detected using the AdaBoost algorithm. An elliptical mask was then used to remove the non-face area of the image. If the contrast was insufficient to produce a full-featured image of the face, the image was enhanced using the Retinex algorithm. This algorithm corrects lighting condition and maintains color constancy. A local binary pattern (LBP) was used to capture the facial features because it positively affects the characteristics of the texture. Employing an LBP is simple and fast; therefore it can be appropriately applied in real-time systems. An SVM classifier was used to train LBP features to accomplish identification. The proposed system is proven to be applicable for access control with satisfactory correct identification accuracy.