搜索资源列表
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Multiresolution Image Segmentation
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K均值聚类算法 由于对纹理图像使用灰度共生矩阵分割效果不明显 因此该算法使用图像频域进行处理-K-means clustering algorithm because of the texture image segmentation using the gray co-occurrence matrix effect was not obvious, therefore use the algorithm for processing images in frequency domain
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Active contour models, deformable surface models,
edge detection, gradient vector flow, image segmentation,
shape representation and recovery, snakes.-Active contour models, deformable surface models, edge detection, gradient vector flow, image s
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K均值 很好用的K均值代码 -K-means K-means used in a very good code
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阈值法实现灰度图像分割，效果不错，可行，可以借鉴-Threshold method to achieve gray-scale image segmentation, the effect of a good, viable, can learn from
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2008年3月
中国图象图形学报
基于类自适应高斯-马尔可夫随机场模型和EM 算法的MR图像分割
比较新的一片关于MARKOV以及EM算法的图像分割的文章。详细介绍了两种算法，以及对MR图像的实验结果，很有参考价值-March 2008 Journal of Image and Graphics of China based on the type of adaptive Gaussian- Markov random field model and the EM algorithm
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Image thresholding has played an important role in image segmentation. In this paper, we present a novel spatially weighted fuzzy c-means (SWFCM) clustering algorithm for image thresholding. The algorithm is formulated by incorporating the spatial ne
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最大流或最小割问题的算法实现，采用graph cut方法做图像分割时需要用到最小割。-Maximum flow or minimum cut algorithm problem, the graph cut image segmentation methods need to use minimum cut.
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Snake的初衷是为了进行图像分割，但它对初始位置过于敏感，且不能处理拓扑结构改变的问题。初始位
置的敏感性可以用遗传算法来克服，因为它是一种全局优化算法，且有良好的数值稳定性。为了更精确地进行图
像分割，本文提出了一种基于遗传算法的双T—Snake模型图像分割方法，它将双T—Snake模型解作为遗传算法的搜
索空间，这既继承了T—Snake模型的拓扑改变能力，又加快了遗传算法的收敛速度。由于它利用遗传算法的全局优
化性能，克服了Snake轮廓局部极小化的缺陷，从而可得到对目标的
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matlab实现图像处理的程序，这是一个关于脑扫描图像分割的程序，很完整-matlab image processing procedures to achieve, this is a brain scan on the image segmentation process, it is a complete
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Image segmentation k mean clustering
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基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理。-Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixe
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Efficient Graph-Based Image Segmentation 一篇论文的代码，修改后，在VS2008运行环境下编译通过-Efficient Graph-Based Image Segmentation paper code, revised in the operating environment under the VS2008 compiler through
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利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。-The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network trainin
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Image segmentation code
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基于区域生长法的MATLAB图像分割程序 -Region growing method based on the MATLAB image segmentation procedure based on the region growing segmentation of the MATLAB program
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基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 -Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixe
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基于一种新的二值化优化方法 与 实现：综合全局二值化与边缘检测的图像分割方法-Based on a new binarization method and the realization of optimization: an integrated global binarization and edge detection for image segmentation method
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A matlab program of image segmentation.
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图像分割，具体算法参考一下论文
Zhi-Gang Tan， Xiao-Chen Heand Nelson H. C. Yung
A Novel Merging Criterion Incorporating Boundary Smoothness and Region Homogeneity for Image Segmentation-Abstract
A novel joint region merging criterion combining region ho
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