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Comparison of Detection Method on Malaria Cell Images

机译:检测方法对疟疾细胞图像的比较

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摘要

In the image analysis process, thresholding is one of the most important preprocessing steps. Thresholding is a sort of picture division that separates protest apportioning a picture into a closer view and foundation. This project will describe a few selected thresholding methods such as Fuzzy C-Mean Algorithm's method, Wolf's method, Bradley's method, Bernsen's method, Triangle's Method and Deghost's Method. Each method will experiment with the malaria image. The objective of thresholding method is to simplify an image into something that is easier to examine. By using MATLAB R2017b as its core programming software, the image will be separated by unused background with uncertainty. The thresholding method will undergo image quality analysis such as Sensitivity and Specificity. Based on numerical anaylsis the Fuzzy C-Mean Algorithm method is more effective and good performance compared to the other methods.
机译:在图像分析过程中,阈值化是最重要的预处理步骤之一。阈值是一种图片划分,将抗议分摊一张图片分开到更近的视图和基础。该项目将描述一些选定的阈值化方法,如模糊C均值算法的方法,狼的方法,布拉德利的方法,伯尔森的方法,三角形的方法和Deghost的方法。每种方法都会试验疟疾形象。阈值化方法的目的是将图像简化为更容易检查的东西。通过使用MATLAB R2017B作为其核心编程软件,图像将通过未使用的背景与不确定性分开。阈值化方法将经过图像质量分析,例如灵敏度和特异性。基于数值ANAYLSIS,与其他方法相比,模糊C均值算法方法更有效且良好的性能。

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