School of Computer Science and Technology, Shandong University, Jinan 250101, China.
Sensors (Basel). 2013 Jul 18;13(7):9248-66. doi: 10.3390/s130709248.
Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT), which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF) is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.
基于视网膜血管的视网膜识别在生物识别中提供了最安全、最准确的认证手段，主要与高安全性设施的门禁系统结合使用。最近，人们对视网膜识别产生了浓厚的兴趣。由于数字视网膜图像总是会发生变形，因此已经引入了 Scale Invariant Feature Transform（SIFT），它以其对尺度和旋转的独特性和不变性而闻名，用于基于视网膜的识别。然而，SIFT 识别存在特征提取困难和不匹配等缺点。为了解决这些问题，提出了一种基于改进的圆形 Gabor 变换（ICGF）的新型预处理方法。经过迭代空间各向异性平滑处理后，大量不相关的 SIFT 关键点被显著减少。在结合旋转和缩放的 VARIA 和八个模拟视网膜数据库上进行测试，所开发的方法显示出了有前景的结果，并且对旋转和尺度变化具有鲁棒性。
