Research on Low Contrast Image Enhancement Algorithm

Finger-vein infrared images have shortcomings such as low signal-to-noise ratio, low ground contrast, and blurred edges. In finger-vein recognition technology, in order to improve the accuracy of finger-vein recognition, the image needs to be enhanced. This paper proposes an image enhancement algorithm based on Gabor filtering and adaptive histogram equalization. Firstly, the image is divided into sub-blocks, and the center frequency of the Gabor filter is set according to the gray gradient of each sub-block to filter the sub-images, and then the adaptive histogram equalization method is used to increase the contrast of finger-vein image. The experimental results show that proposed method can effectively improve the edge definition and contrast of the image while suppressing the noise signal of the finger vein image, and the effect of vein image enhancement is well improved.