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Localization of the optic disc center in retinal images based on the Harris corner detector

机译:基于哈里斯角检测器的视网膜图像视盘中心定位

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Purpose: Localizing the optic disc and its center is the first step of most identification, segmentation algorithms and diagnosing some diseases on fundus photographs such as diabetic retinopathy. Despite the importance of optic disc localization, there is not very accurate and fast method for localizing the center of optic disc in retinal images. Therefore, we propose a robust and fast algorithm for localizing the center of optic disc. Methods: Based on the property of optic disc, vessels originate from the center of optic disc and the number of the vessels in the vicinity of optic disc is more than others regions in the retinal images. Therefore, we can see the largest number of corners and bifurcations around the optic disc in the retinal images. In this paper, a robust method based on Harris corner detector is proposed. Using the Harris corner detector, corners and bifurcations are found in the retinal images. Then, we use a moving window near the size of optic disc to count the number of corners. Finally, the center of windows in which the high number of corners are located, is obtained and the mean of these centers is considered as the center of optic disc. The DRIVE, STARE and a local dataset including 273 retinal images are used to evaluate the proposed algorithm. Results: The success rate is 97.5%, 87.65% and 97.8% for DRIVE, STARE and a local dataset. The average distance between the estimated and the manually identified optic disc centers is 4.61, 11 and 9 pixels for the DRIVE, STARE and local dataset respectively. Comparing the results of our proposed method and counterpart methods verifies the effectiveness of the proposed method. Conclusions: In this paper, we proposed a new method for localizing the center of optic disc based on corners and bifurcations obtained using Harris corner detector. Comparing the results of our proposed method and counterpart methods verifies the effectiveness of the proposed method.
机译:目的:对视盘及其中心进行定位是大多数识别,分割算法和诊断眼底照片上的某些疾病(例如糖尿病性视网膜病)的第一步。尽管视盘定位很重要,但是在视网膜图像中还没有非常准确和快速的方法来定位视盘中心。因此,我们提出了一种鲁棒且快速的算法来定位光盘中心。方法:根据视盘的性质,血管起源于视盘中心,视盘附近的血管数量多于视网膜图像中的其他区域。因此,我们可以在视网膜图像中看到视盘周围最大数量的角和分叉。提出了一种基于Harris角点检测器的鲁棒方法。使用哈里斯拐角检测器,可以在视网膜图像中发现拐角和分叉。然后,我们使用光盘大小附近的移动窗口来计算转角数量。最终,获得具有大量拐角的窗口的中心,并且将这些中心的平均值视为光盘的中心。 DRIVE,STARE和包含273个视网膜图像的本地数据集用于评估所提出的算法。结果:DRIVE,STARE和本地数据集的成功率分别为97.5%,87.65%和97.8%。对于DRIVE,STARE和本地数据集,估计的光盘中心和手动识别的光盘中心之间的平均距离分别为4.61、11和9像素。比较我们提出的方法和相应方法的结果,验证了提出方法的有效性。结论:在本文中,我们提出了一种新的基于哈里斯角检测器获得的角和分叉来定位光盘中心的方法。比较我们提出的方法和相应方法的结果,验证了提出方法的有效性。

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