相干增强扩散与冲击滤波相结合的指纹增强算法

自动指纹识别系统(AFIS)的性能严重依赖于输入指纹的质量,因此有效指纹增强算法对该系统具有重要意义。针对相干增强扩散滤波增强的指纹图像会出现边缘模糊,以及谷线与脊线间对比度较低的现象,提出使用冲击滤波和相干增强扩散的加权模型方法,既能保持相干增强扩散的优势,又能锐化指纹脊线边缘,以及增强指纹脊线与谷线的对比度。增强的主要过程为,建立一个相干增强扩散和冲击滤波的加权组合模型,加权函数是以指纹梯度为自变量,使得在扩散过程中在图像边缘处以冲击滤波为主,在脊线与谷线内部则以相干增强扩散为主。实验表明,使用这种方法,能得到更加清晰的指纹图像,便于之后的二值化与细化过程处理,使得自动指纹识别系统具有更好的性能。

Fingerprint Enhancement Using Shock Filter with Coherence Enhance Diffusion

The performance of automatic fingerprint identification system is heavily determined by the quality of the input image, thus an effective method to enhance the fingerprint image is essential in such a system. Since the method of fingerprint image enhancement of coherence-enhancing diffusion has the disadvantages that the enhanced image will appear blurring edges and low contrast between ridges and valleys of fingerprint images, a new method combining coherence-enhancing diffusion and shock filter is put forward which can not only maintain an advantage of coherence-enhancing diffusion, but sharpen edges and enhance the contrast between ridges and valleys. Thus novel approach comes out. First, a weighting model of combining coherence-enhancing diffusion with shock filter is bulit, which emphasizes particularly on shock filter at edges while on coherence-enhancing diffusion at the other part , and gradient is taken as automatic variable of weighting function.Experimental results show that the proposed combining approach can obtain a more clear fingerprint image which is convenient to the process of binarization and thinning and finally achieve a better performance of the system.