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A Segmentation Technique of Retinal Blood Vessels using Multi-Threshold and Morphological Operations

机译:基于多阈值和形态学运算的视网膜血管分割技术

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Retinal blood vessels are one of the most significant features in the fundus image of the eye, which plays a crucial role in the early screening of different ocular diseases like glaucoma, diabetic retinopathy, cataract and hypertensive retinopathy. Also in the area of biometric systems, blood vessel structure plays a vital role as retina scan is one of the finest and reliable methods. This paper proposed a segmentation technique which accurately extracts retinal blood vessels. The proposed algorithm conducted in three phases (i) pre -processing of image using AHE, CLAHE and average filtering, (ii) Multi-threshold based novel segmentation technique is used and (iii) post processing is done to remove the imperfections and for this morphological operation is employed. This method efficiently segments the vessels and improves the performance parameters. The accuracy of 95.3% is achieved. Implementation part was done in MATLAB 2015a using a DRIVE database openly available online.
机译:视网膜血管是眼底图像中最重要的特征之一,它在早期筛查各种眼病如青光眼,糖尿病性视网膜病,白内障和高血压性视网膜病中起着至关重要的作用。同样在生物识别系统领域,血管结构也起着至关重要的作用,因为视网膜扫描是最可靠的方法之一。本文提出了一种可准确提取视网膜血管的分割技术。所提出的算法分三个阶段进行(i)使用AHE,CLAHE和平均滤波对图像进行预处理,(ii)使用基于多阈值的新颖分割技术,并且(iii)进行后处理以消除缺陷,为此采用形态学操作。该方法有效地分割了血管并改善了性能参数。达到95.3%的精度。在MATLAB 2015a中使用在线上公开可用的DRIVE数据库完成了实现部分。

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