Dynamic Local Feature Analysis for Face Recognition

This paper introduces an innovative method, Dynamic Local Feature Analysis (DLFA), for human face recognition. In our proposed method, the face shape and the facial texture information are combined together by using the Local Feature Analysis (LFA) technique. The shape information is obtained by using our proposed adaptive edge detecting method that can reduce the effect on different lighting conditions, while the texture information provides the details of the normalized facial feature on the image. Finally, both the shape and texture information is combined together by means of LFA for dimension reduction. As a result, a high recognition rate is achieved no matter the face is enrolled under different or bad lighting conditions.

• Type: Conference
• Year: 2004
• Where: ICBA
• Authors: Johnny Ng, Humphrey Cheung
• Keywords: Biometrics, ICBA 2004, Lighting Conditions, Local Feature Analysis, Texture Information