Based on maximum between-cluster variance method and uniformity measure, this paper USES maximum entropy principle to select the gray-level threshold value for image segmentation.
在最大类间方差法和一致性准则法的基础上，运用最大熵原理来选择灰度阈值对图像进行分割。
Combining the two essential characteristics of the image, the gradient and the gray level, a threshold segmentation approach using maximum entropy with the gradient boundary control was proposed.
结合梯度和灰度这两种图像的本质特征，提出一种基于边界梯度控制的最大熵阈值分割方法。
It presents a new region growing algorithm with gray level co-occurrence matrix to extract the focus region, the threshold segmentation is applied to improve the edge of segmented region.
为了提取局部感兴趣区域，给出了一种基于灰度层共现矩阵的区域增长算法，分割出病灶区域，再结合迭代阈值算法进行病灶边界的磨合。
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