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An image segmentation method based on maximizing fuzzy correlation and its fast recursive algorithm

机译:基于最大化模糊相关性的图像分割方法及其快速递归算法

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摘要

In this paper, an image segmentation method is proposed that integrates fuzzy 2-partition into Yen's maximum correlation thresholding method. A fuzzy 2-partition of the image is obtained by transforming the image into fuzzy domain by means of two parameterized membership functions. Fuzzy correlation is defined to measure the appropriateness of the fuzzy 2-partition. An ideal threshold is calculated from the optimal membership functions' parameters, which make the corresponding fuzzy 2-partition have maximum fuzzy correlation. In the process of searching the optimal parameters of membership functions, a fast recursive algorithm is presented in order to reduce the computation complexity. Experimental results on synthetic image, brain magnetic resonance (MR) images and casting images show that the proposed method has a satisfactory performance.
机译:本文提出了一种图像分割方法,该方法将模糊2分割集成到Yen的最大相关阈值化方法中。通过使用两个参数化的隶属度函数将图像转换为模糊域,可以获得图像的模糊2分。定义了模糊相关以测量模糊2分区的适当性。根据最优隶属度函数的参数计算出一个理想阈值,使相应的模糊2-划分具有最大的模糊相关性。在寻找隶属函数的最优参数过程中,提出了一种快速递归算法,以降低计算复杂度。在合成图像,脑磁共振图像和投射图像上的实验结果表明,该方法具有令人满意的性能。

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