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Localizing Optic Disc in Retinal Image Automatically with Entropy Based Algorithm

机译:基于熵的算法自动定位视网膜图像中的光盘

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Examining retinal image continuously plays an important role in determining human eye health; with any variation present in this image, it may be resulting from some disease. Therefore, there is a need for computer-aided scanning for retinal image to perform this task automatically and accurately. The fundamental step in this task is identification of the retina elements; optical disk localization is the most important one in this identification. Different optical disc localization algorithms have been suggested, such as an algorithm that would be proposed in this paper. The assumption is based on the fact that optical disc area has rich information, so its entropy value is more significant in this area. The suggested algorithm has recursive steps for testing the entropy of different patches in image; sliding window technique is used to get these patches in a specific way. The results of practical work were obtained using different common data set, which achieved good accuracy in trivial computation time. Finally, this paper consists of four sections a section for introduction containing the related works, a section for methodology and material, a section for practical work with results, and a section for conclusion.
机译:检查视网膜图像在确定人眼健康方面持续发挥着重要作用;如果此图像中存在任何变化,则可能是某些疾病引起的。因此,需要计算机辅助扫描视网膜图像以自动和准确地执行该任务。此任务的基本步骤是识别视网膜元素。光盘本地化是此识别中最重要的一项。已经提出了不同的光盘定位算法,例如将在本文中提出的算法。该假设基于光盘区域具有丰富的信息这一事实,因此其熵值在该区域中更为重要。该算法具有递归步骤,可以测试图像中不同斑块的熵。滑动窗口技术用于以特定方式获取这些补丁。通过使用不同的通用数据集获得了实际工作的结果,从而在琐碎的计算时间上获得了良好的准确性。最后,本文由四个部分组成,一个是包含相关工作的引言部分,一个是方法论和材料的部分,一个是有成果的实际工作的部分,另一个是结论的部分。

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