Research and Improvement on the Algorithm of Face Gray Image Normalization

Abstract

In face recognition system, the purpose of gray pretreatment is to denoise and enhance the image. The traditional linear or nonlinear denoising algorithm can bring edge loss, which make it difficulty for the subsequent image segmentation or matching. Although Alpha filter can bring the minimum loss of image edge, the size of filtering window cannot be adaptively changed according to the noise. The Alpha filter is improved on the basis that the information entropy can reflect the noise strength to some degrees. The single pixel entropy in neighborhood is compared with the information entropy average and then the noise infection of neighborhood pixel is determined. Moreover, according to the noise infection, the window size is adaptively adjusted to filter. The results show that the loss of image edge obviously reduces. Because the image size is fixed, we can calculate the integration of normalized image according to cumulative distribution function of the image. Therefore, the image histogram equalization is derived and the image gray is transformed to get the enhanced image. Finally, the results show that the face image after improved gray pretreatment can well ensure the image edge integrity and the face recognition effect is improved by edge feature.