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Determination of number of clusters in K-Means Clustering and Application in color image segmenta
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基于内容的图像识别特征提取部分——k-均值聚类分割获取形状等信息-Content-based image recognition, feature extraction part of- k-means clustering segmentation information for shape
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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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matlab编写的纹理图像分割gussian滤波后k-means聚类并将不同区域用线条表示出来除m程序还包括测试图片-matlab prepared texture image segmentation gussian filtered k-means clustering will be expressed in different regions of the use of lines, inter m program also includes test pictures
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这是K-means聚类算法的源代码，可实现任意多统计数据的归类处理。代码为原创，用途主要在数理统计方面，而不是常见的图像处理等方面。内附详细的使用说明。-This is the K-means clustering algorithm source code, enabling the classification of any number of statistical data processing. Code for my original, uses mainly in mathemat
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对电路板的图像进行分割，可以提取电路板中的目标物，以对电路板进行检测。文章使用K均值聚类算法完成对电路板图像的分割，针对传统的K均值聚类算法的不足，提出了使用直方图波形的有效波峰个数来确定K值的大小，并通过使用一种比传统的绝对误差的表示更简洁的表达式，达到了快速分割的目的。对一些电路板图像分割的实验结果表明，文章的方法能够根据目标物的数目有效的确定K值的大小，且比传统的K均值算法减少了运算量及计算时间。-On the circuit board image segmentation, to ex
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code for image clustering using k-means
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ector quantization is a classical quantization technique from signal processing which allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a l
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KMEANSK Performs K-means clustering given a list of feature vectors and k
The argument k indicates the number of clusters you want the data to be
divided into. data_vecs (N*R) is the set of R dimensional feature
vectors for N data points. E
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使用k均值法对一组数据进行聚类，画出结果图像-Use the k-means clustering, a set of data to draw the resulting image
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The attachment consists of a source code that performs malarial segmentation using k-means clustering.It also contains HUI conversion of an malarial image.Water shed algorithm applied on a cel image , and detection of water ridge lines for dental x r
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This paper presents a new approach to image segmentation using Pillar K-means algorithm. This
segmentation method includes a new mechanism for grouping the elements of high resolution images in order to
improve accuracy and reduce the computation
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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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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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表示出两帧图像间各个像素点的相对情况，基于K均值的PSO聚类算法,实现了图像的加水印，去噪，加噪声等功能。- Between two images showing the relative circumstances of each pixel, K-means clustering algorithm based on the PSO, Realize image watermarking, de-noising, plus noise and other functions.
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In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing M
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用kmeans算法处理资源3号卫星图像，用欧式距离来计算聚类中心，在用前后两次聚类之间的误差来决定迭代次数(Kmeans algorithm is used to deal with the resource 3 satellite image, and the Euclidean distance is used to calculate the clustering center. The number of iterations is determined by the error bet
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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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Color Reduction and Quantization using k-Means, Fuzzy Clustering (FCM), and SOM Neuarl Network in MATLAB
In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent c
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