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Used for OpenCV gaussian background foreground segmentation-Used for OpenCV gaussian background foreground segmentation
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基于熵的图像分割方法有很多，Tsallis灰度熵是其中的一种，它与其他传统熵相比，考虑了图像中目标和背景类内灰度级的均匀性-There are many entropy-based image segmentation method, Tsallis grayscale entropy is one of them。 Compared with other traditional methods, it considering the target image and the backgroun
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利用基于直方图的自适应阈值方法实现分割前景与背景-The use of adaptive threshold method of histogram based segmentation of foreground and background
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这是一个简单的图像分割程序，对于背景不复杂的图像效果不错！-This is a simple image segmentation procedure, to the image effect of complex background is not good!
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自适应阈值分割可以根据图像自身的特性得到自适应阈值进而分割出目标和背景。-Adaptive threshold segmentation is based on the characteristics of the image itself to get the adaptive threshold and then segmentation the target and background.
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根据概率密度分布，分割前景与背景，附有实验图片-According to a probability density distribution, segmentation foreground and background, experiment with picture
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用U-net进行脑部图像多类分割，用keras框架进行实现(U-net brain segmentation keras tensorflow background)
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OTSU算法也称最大类间差法，有时也称之为大津算法，被认为是图像分割中阈值选取的最佳算法，计算简单，不受图像亮度和对比度的影响，因此在数字图像处理上得到了广泛的应用。它是按图像的灰度特性,将图像分成背景和前景两部分.(Difference method OTSU algorithm called maximum class, sometimes called the Otsu algorithm, is considered to be the best algorithm, threshold
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