Experimental results show that the segmentation quality of some images using new fuzzy entropy thresholding method is better than that of classical fuzzy entropy.
实验结果表明，该修改是可行的，对有些图像相对求和型模糊熵分割法能获得更好的分割效果。
Entropy thresholding method is an automatic technique for thresholding of digital images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
它包括二维匹配滤波预处理以增强血管的灰度，以及用灰度-梯度共生矩阵的最大熵阈值化方法。
Image thresholding segmentation method based on fuzzy partition entropy has good segmentation performance and becomes a kind of extensive application method in image segmentation field.
基于模糊划分熵的图像阈值化分割方法因具有良好的分割性能已成为图像分割广泛应用的方法之一。
The method eliminates impulse noises by median filtering then extracts edges by Otsu's thresholding based on local entropy of image, connects discrete edges and detects objects regions.
该方法首先进行中值滤波消除图像脉冲噪声，然后计算图像局部熵进行阈值选择提取目标边缘，最后进行边缘连接分割出目标区域。
Experimental results show that the thresholding method based on relative entropy coefficient in this paper is feasible.
实验结果表明，本文提出的关联熵系数阈值分割方法是可行的。
Experimental results show that the thresholding method based on relative entropy coefficient in this paper is feasible.
实验结果表明，本文提出的关联熵系数阈值分割方法是可行的。
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