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3下载:
用k-means 做彩色图像分割,分类数可选,Using k-means to do color image segmentation, classification number of optional
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本程序实现了K均值(HCM)算法,ISODATA算法,模糊C均值(FCM),模糊阈值法等对遥感影像的分割。,This program implements K means (HCM) algorithm, ISODATA algorithm, fuzzy C means (FCM), fuzzy threshold law of remote sensing image segmentation.
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基于matlab的图像k均值算法,实现对一副彩色图像进行分割。-Matlab image based on k means algorithm, to realize a color image segmentation.
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本实验基于K-Means聚类算法思想实现了字符分割,因为车牌规定是7位的,所以K取7。另外本实验对K-Means算法进行了改进,充分考虑了初始点的设置及迭代结束条件。实验结果证明这种改进的K-Means算法实现车牌字符分割是快速、有效的。-In this study, K-Means clustering algorithm based on the ideology of the character segmentation, because the license plate require
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k均值图像分割,经典的图像分割方法,算法简单,效果好。-k-means image segmentation
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利用相位一致性提取图像边缘,K-means聚类后区域生长进行图像分割,附参考论文。-Using phase coherence image edge extraction, K-means clustering image after region growing segmentation, attached reference paper.
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K-meansK均值聚类在无监督的情况下选择图像特征的算法-K-meansK means clustering in the case of unsupervised image feature selection algorithm
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基于K均值算法和互信息熵差的算法,可以有效地确定分类数,从而该算法对医学图像进行自动优化分割。-K means algorithm based on entropy and mutual information algorithms, can effectively determine the classification number, so that the algorithm for automatic optimization of medical image segmentation.
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K均值算法实现图像的分割,分割效果可以达到预期的效果-K-means algorithm to achieve image segmentation, segmentation results can be achieved the desired results
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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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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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k-means segmentation example
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k-mean Algorithm for segmentation of digital image
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k-means Clustring sub routine very useful Texture Image Segmentation
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台湾大学几位学者写的基于K-均值算法的快速图像分割,用到基于HSV颜色空间的直方图-Fast Image Segmentation Based on K-Means
Clustering with Histograms in HSV Color Space
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segmentation of brain from MRI image using k-means-segmentation of brain from MRI image using k-means
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Clustering is a way to separate groups of objects. K-means clustering treats each object as having a location in space. It finds partitions such that objects within each cluster are as close to each other as possible, and as far from objects in other
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该代码实现了k-means聚类算法对图像的分类处理,同时通过RMSE和准确性对比对技术的表现和准确度进行了测试-The code implements the k-means clustering algorithm to classify the image. At the same time, the performance and accuracy of the technique are tested by RMSE and accuracy comparison.
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k-means 聚类和分割的图像处理方法(k-means and segement image process)
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增加椒盐噪声对图像进行去噪处理后,实现图像分割(Adding salt and pepper noise to image denoising,realization of image segmentation)
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