Long-distance/environment face image enhancement method for recognition

Abstract

With the increase of distance and the influence of environmental factors, such as illumination and haze, the face recognition accuracy is significantly lower than that of indoor close-up images. In order to solve this problem, an effective face image enhancement method is proposed in this paper. This algorithm is a nonlinear transformation which combines gamma and logarithm transformation. Therefore, it is called: G-log. The G-Log algorithm can perform the following functions: (1) eliminate the influence of illumination; (2) increase image contrast and equalize histogram; (3) restore the high-frequency components and detailed information; (4) improve visual effect; (5) enhance recognition accuracy. Given a probe image, the procedure of face alignment, enhancement and matching is executed against all gallery images. For comparing the effects of different enhancement algorithms, all probe images are processed by different enhancement methods and identical face alignment, recognition modules. Experiment results show that G-Log method achieves the best effect both in matching accuracy and visual effect. Long-distance uncontrolled environment face recognition accuracy has been greatly improved, up to 98%, 98%, 95% for 60-, 100-, 150-m images after processed by G-Log from original 95%, 89%, 70%.