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进行kcm和fcm聚类分割图象的性能比较-kcm for clustering segmentation and image fcm Performance Comparison
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模糊聚类的图像分割,用matlab语言编写实现模糊聚类的图象分割。,Fuzzy clustering image segmentation, matlab language used to achieve fuzzy clustering image segmentation.
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图像分割算法之间的比较，比较前沿的放发，利用了kmeans和模糊K均值,Between the image segmentation algorithm compares the release cutting-edge hair, use a K-means and fuzzy kmeans
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matlab programming for clustering pam , k-means , dbscan , optics for image segmentation
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聚类PPT,包括五种算法，和几种软件的实现。实用。-Clustering PPT, including the five algorithms, and several software implementations. Practical.
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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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本程序首先把图像由RGB空间转到HSI空间，然后利用彩色图像分割策略以及meanshift算法对图像进行分割最后加入边界合成。其中‘keyprogram.m’文件为主程序，‘meanshift.m’文件为调用函数，实现数据的聚类分割。-The program first the image from the RGB space to HSI space and then using color image segmentation strategy and meanshift image seg
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Image segmentation by clustering
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通过模糊c-均值（FCM）聚类实现图像的分割。-Through the fuzzy c-means (FCM) clustering to achieve image segmentation.
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k-均值聚类法用于各种图像的聚类、分割问题，希望可以对您有利-k-means clustering method for a variety of image clustering, segmentation
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将K均值算法用于图像分割,输入的是彩色图像,转换为灰度图像进行分割,输出结果为灰度图像.利用灰度做为特征对每个像素进行聚类,由于光照等原因,有时应该属于一个物体的像素,其灰度值也会有很大的差别,可能导致对该像素的聚类发生错误.在分割结果中,该物体表面会出现一些不同于其它像素的噪声点,因此,算法的最后,对结果进行一次中值滤波,以消除噪声,达到平滑图像的作用-The K means algorithm for image segmentation, the input is a color imag
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在matlab平台下实现的FCM（模糊C均值）聚类分割-In the matlab platform to achieve FCM (fuzzy C mean) clustering segmentation
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KMeans图像聚类分割：用K-Means聚类方法来对图像进行分割。主要是对图像的颜色进行聚类。开发环境：VC6，需要安装OpenCV。-KMeans clustering in image segmentation: with K-Means clustering approach to image segmentation. Mainly the color of the image cluster. Development Environment: VC6, need to install
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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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to segment images by ,form"A factorization approach to grouping",
and "Segmentation Using Eigenvectors: A Unifying View", UC
Berkeley.-to segment images by Spectral Clustering,form"A factorization approach to grouping",
and "Segmentation
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K-means算法是一种动态聚类方法，这种方法先选择若干样本作为聚类的中心，在按某种聚类准则（通常采用最小距离原则）使各种样本向各个中心积聚，从而得到初始的分类，然后，判断分类的合理性，如果不合理，就修改分类，如此反复的修改聚类的迭代运算，直到合理为止。-K-means algorithm is a dynamic clustering method, this method, select the number of samples as a cluster center in the clu
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模糊聚类分割主函数及demo，直接运行就行，当然要有图片，-Main functions and fuzzy clustering segmentation demo, run directly on the line, of course, have pictures, Oh
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matlab程序代码 聚类分割程序 图形聚类分割-the matlab code clustering segmentation graphics Clustering Segmentation
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自己编写模糊聚类的图像分割，图像处理课程的作业，能分割车牌图和细胞图-Write your own fuzzy clustering image segmentation, image processing course of assignments, to license plate image and cell image segmentation
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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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