Improvement of face recognition using light compensation technique on real-time imaging

Camera imaging systems are used widely. However, the resulting images may show unequal light distributions due to backlight. In this paper, an adaptive backlight compensation algorithm is presented for fixing the brightness and contrast in regions of interest, particularly for human faces. The framework is implemented in two stages. The first stage is the light compensation algorithm, which depends on face detection and focuses on the intensities of pixels in ‘face’ regions only. The second stage uses a distance weighting approach to address artificial light effects created by the first stage. This algorithm can adjust the imaging light distribution adaptively in order to solve the problem of backlight and achieve natural-looking pictures. For face recognition systems, this approach can improve the success rate for face recognition by 35% on average when images are backlit.