Gabor filter

The article is devoted to the development of biometric identification methods based on new filtration methods. Biometric identification systems need constant improvement, because they often work slowly and give the wrong result. To increase the reliability of biometric image recognition, the method is formed, which is formed from the stages: segmentation, normalization, local orientation estimation, local estimation, spine frequency estimation, Gabor filter implementation, binarization, thinning.

Lighting Normalization is an especially important issue in the image recognitions systems since different illumination conditions can significantly change the recognition results, and the lighting normalization allows minimizing negative effects of various illumination conditions. In this paper, we are evaluating the recognition performance of several lighting normalization methods based on the Self-Quotient ImagE(SQI) method introduced by Haitao Wang, Stan Z. Li, Yangsheng Wang, and Jianjun Zhang.