Finger Vein Image Inpainting with Gabor Texture Constraints

Abstract

The texture edge continuity of a finger vein image is very important for the accuracy of feature extraction. However, the traditional inpainting methods which, without accurate texture constraints, are easy to cause the vein texture of the inpainted image to be blurred and break. A finger vein image inpainting method with Gabor texture constraints is proposed. The proposed method effectively protects the texture edge continuity of the inpainted image. Firstly, using the proposed vertical phase difference coding method, the Gabor texture feature matrix of the finger vein image, which can accurately describe the texture information, can be extracted from the Gabor filtering responses. Then, according to the local texture continuity of the finger vein image, the known pixels, which have different texture orientations with the center pixel in the patch, are filtered out using the Gabor texture constraining mechanism during the inpainting process. The proposed method eliminates irrelevant information interference in the inpainting process and has a more precise texture propagation. Simulation experiments of artificially synthetic images and acquired images show that the finger vein images inpainted by the proposed method have better texture continuity and higher image quality than the traditional methods which do not have accurate texture constraints. The proposed method improves the recognition performance of the finger vein identification system with the acquired damaged images.