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Extraction and Classification of Blood Vessel Minutiae in the Image of a Diseased Human Retina

机译:患病人视网膜形象中血管细节的提取与分类

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The work presents a created methodology for detecting minutiae in the image of the retina of a sick person's eye. The worked out algorithm is used to find areas of distribution and classification of minutiae in ill human eye retinal image. The main goal of the proposed approach is to classify all minutiae into groups based on the distance from the center of the image and the distance from the edge of the image that is closer to the blind spot. For the separation of blood vessels from the image, Otsu algorithm and background subtraction were used. To get line representation of blood vessels that helps find minutiae in images, the K3M thinning algorithm was used. The proposed algorithm shows one of the most basic solutions for finding the characteristic points in a biometric image. The last step of the presented algorithm introduces an example of minutiae classification.
机译:该工作提出了一种为检测病人眼睛视网膜图像中的细节的创造方法。所做的算法用于找到生病的人眼视网膜图像中细节的分布和分类领域。所提出的方法的主要目的是基于从图像中心的距离和距离盲点的图像边缘的距离来将所有细节分为组。为了从图像中分离血管,使用OTSU算法和背景减法。为了获得有助于在图像中找到细节的血管的血管呈现,使用K3M稀释算法。所提出的算法示出了用于在生物识别图像中找到特征点的最基本解决方案之一。所提出的算法的最后一步介绍了细节分类的一个例子。

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