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基于K均值聚类的图像检索：用K均值聚类方法提取图像特征进行检索-K-means clustering - based Image Retrieval : K-means clustering method of extracting image features Search
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国外的一个图像K均值聚类的C++源代码，非常容易集成和使用，适合模式识别、图像处理等方面的开发！-an image abroad of K-means clustering of C source code, and is easy to integrate and use, suitable for pattern recognition, Image processing, and other aspects of development.
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Determination of number of clusters in K-Means Clustering and Application in color image segmenta
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通过将一幅图像的sift特征提取出来，然后对他们采用k均值方法进行聚类,By an image feature extraction sift out, and then on their way to the use of k-means clustering
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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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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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所上传文件包包括6种vc++源代码：使用opencv的实现可视图的静态路径规划；简单的svm算法；基于vc2008的图像匹配（多工程结构）；基于局部搜索的K-means聚类算法；三维匹配中的ICP算法；视觉tracking中的condensation算法-Upload file package, including the six kinds of vc++ source code: using opencv to view the realization of the static path
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usefull k-mean algorithm developed for image clustering using java
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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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code for image clustering using k-means
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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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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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此代码为matlab代码，分为两个部分。第一部分实现K均值聚类算法应用它来压缩图像。在第二部分中，你将使用主成份分析法pca来实现人脸图像的低维表示。
-This code for the matlab code, is divided into two parts. The first part of the implementation of the K means clustering algorithm to compress the image. In the second par
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将K-means聚类算法应用于图像的分割，留有较多的其他特征接口。-The K-means clustering algorithm is applied to image segmentation, leaving more other features of the interface.
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一种k-means聚类算法的图像分割例程，很好用。里面包括主函数和子函数的m文件以及使用的图片。-One kind of k-means clustering image segmentation algorithm routines, very good use. Which includes the main functions and subroutines m documents and pictures used.
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实现图像的Kmeans聚类，完美实现图像分割-The K Means clustering of image, the perfect image segmentation
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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算法是很典型的基于距离的聚类算法，采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大(K-means algorithm is a typical distance based clustering algorithm. The distance is used as the evaluation index of similarity, that is, the closer the distance between the two objects, the
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Andrew Ng Cousera 机器学习K-means勇于图像压缩 以及主成分分析PCA用在人脸识别，源代码以及说明文档。(Andrew Ng Cousera machine learning , the K-means clustering algorithm and apply it to compress an image. In the second part, you will use principal component analysis to find a low-dime
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