论文标题
通过结合LBP和猪的视网膜血管进行识别
Identification via Retinal Vessels Combining LBP and HOG
论文作者
论文摘要
随着信息技术的发展和高安全性的必要性，使用不同的识别方法变得非常重要。每个生物识别特征都有其自身的优势和缺点，并且选择它们都取决于我们的用法。视网膜扫描是用于识别的生物量表方法。视网膜由血管和光盘组成。血管分布模式是一种显着的视网膜识别方法。在本文中，提出了一种新方法，用于使用LBP和HOG方法通过视网膜图像进行识别。在提出的方法中，将尝试通过机器视觉技术准确地分离视网膜容器，该技术将在旋转和尺寸变化方面具有良好的可持续性。基于HOG或基于LBP的方法或它们的组合可以用于分离，也可以使用HSV颜色空间。提取功能后，可以将相似性标准用于识别。所提出的方法的实施及其与该领域新呈现方法之一的比较显示了该方法的更好性能。
With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.
