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用于图像处理，K-MEANS聚类实现图像的分割和识别，是一种重要的图像处理方法-For image processing, K-MEANS Clustering achieve image segmentation and recognition, is an important image processing method
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实现图像的分割。改程序是在matlab环境下运行的，程序中用到了k-means算法，实现的结果很不错-This is the program of image segmentation based on the following work:
S. Chen, L. Cao, J. Liu, and X. Tang, "Image Segmentation by MAP-ML Estimations", submitted to IEEE Transactions on Image P
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kmeans image segmentation
Input:
ima: grey color image
k: Number of classes
Output:
mu: vector of class means
mask: clasification image mask- kmeans image segmentation
Input:
ima: grey color image
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迫零和最小均方误差比较，非常好的程序，保证可以仿真出图形-DIP text book kmeans image segmentation Input: ima: grey color image k: Number of classes Output: mu: vector of class means mask:
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利用libsvm进行图像分割，其结果比k-means以及fcm都要好一点-libsvm to image segmentation
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该方法采用gabor提取出图像纹理特征，最后采用k-means方法聚类进行图像分割(The method uses gabor texture features extraction, and finally using k-means clustering methods for image segmentation)
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