Two-Stage Enhancement Scheme for Low-Quality Fingerprint Images by Learning From the Images
Two-Stage Enhancement Scheme for Low-Quality Fingerprint Images by Learning From the Images
复制标题
通过图像学习的低质量指纹图像两阶段增强方案
DOI：
10.1109/tsmcc.2011.2174049
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发表时间：
2013-03-01
影响因子：
3.6
通讯作者：
Vasilakos, Athanasios V.
中科院分区：
文献类型：
--
作者：
Yang, Jucheng;Xiong, Naixue;Vasilakos, Athanasios V.
用于人机系统、控制论和计算智能中的内容保护的指纹认证非常流行。由于输入环境复杂，低质量的输入指纹图像总是存在裂纹和疤痕、皮肤干燥或脊线和谷部对比度差的脊线。通常，指纹图像在空间域或频域中增强一级。然而，由于复杂的脊结构受到异常输入上下文的影响，增强的性能并不令人满意。在本文中，我们通过从底层图像中学习，提出了一种新颖且有效的空间域和频域两阶段增强方案。为了修复脊线区域并增强局部脊线的对比度，我们首先通过从图像中学习，使用空间脊线补偿滤波器来增强空间域中的指纹图像。在第一步的帮助下，采用第二级滤波器，即在径向和角频率域中可分离的频带通滤波器。值得注意的是，带通滤波器的参数是从原始图像和第一级增强图像两者中学习的，而不是仅从原始图像获取。由于滤波器在径向和角频率域中的快速且急剧的衰减，它显着增强了指纹图像。实验结果表明，我们提出的算法能够处理各种输入图像上下文，与公共数据库上的一些最先进的算法相比，取得了更好的结果，并提高了指纹认证系统的性能。
Fingerprint authentication for content protection in the human-machine systems, cybernetics, and computational intelligence is very popular. Because of the complex input contexts, low-quality input fingerprint images always exist with cracks and scars, dry skin, or poor ridges and valley contrast ridges. Usually, fingerprint images are enhanced by one stage in either the spatial or the frequency domain. However, the enhanced performances are not satisfactory because of the complicated ridge structures that are affected by unusual input contexts. In this paper, we propose a novel and effective two-stage enhancement scheme in both the spatial domain and the frequency domain by learning from the underlying images. To remedy the ridge areas and enhance the contrast of the local ridges, we first enhance the fingerprint image in the spatial domain with a spatial ridge-compensation filter by learning from the images. With the help of the first step, the second-stage filter, i.e., a frequency bandpass filter that is separable in the radial- and angular-frequency domains, is employed. It is noted that the parameters of the bandpass filters are learnt from both the original image and the first-stage enhanced image instead of acquiring from the original image solely. It enhances the fingerprint image significantly because of the fast and sharp attenuation of the filter in both the radial and the angular-frequency domains. Experimental results show that our proposed algorithm is able to handle various input image contexts and achieves better results compared with some state-of-the-art algorithms over public databases, and to improve the performances of fingerprint-authentication systems.