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matlab中使用k-means聚类实现图像分割-using k-means clustering matlab image segmentation
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k均值聚类二值化字符图像,通过把RGB图像分割成不同区域-k-means clustering binarized character image, by RGB image segmentation into different regions
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将彩色图像,转化到Lab空间,利用K-means类聚对图像进行分割-The color image is transformed into Lab space, the use of the class of K-means poly image segmentation
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K means+PSO for Image Segmentation
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Image Segmentation using K means
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基于K-means聚类的图像分割算法,想法比较简单,实现很方便,运行速度很快,有例图。-Image segmentation based on K-means clustering algorithm, the idea is relatively simple, very convenient, fast run case diagram.
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首先进行帧差处理,根据得到的帧差进行k均值算法,完成图像分割-First frame difference processing, k-means algorithm based on frame difference, to complete the image segmentation
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图像分割中K-means聚类算法的matlab实现-Image segmentation in the K-means clustering algorithm matlab implementation
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k 均值算法用于图像分割,根据灰度图自适应地确定分类数并进行分割,需要先用k均值初始化-k’-means algorithm for image segmentation, based on grayscale adaptively determine the number of classification and segmentation, you need to use the k-means initialization
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使用k-means方法对图像进行分割,可以得到较为不错的效果-Using k-means method for image segmentation, good results can be obtained more
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使用K-means聚类方法实现图像分割,代码可用,操作简单-Using K-means clustering method of image segmentation, the code is available, easy to operate
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利用k-means的算法实现图像区域分割,主程序只能运行灰度图像,彩色图像需另写调用程序-Using the k-means algorithm for image segmentation, the main program will only run grayscale image, color image subject to write the calling program
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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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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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用c#和emgucv实现了hough变换检测圆和最大类间方差和k均值聚类分割图像,k均值聚类的函数可填写分类数和迭代次数的阈值,而且是基于灰度的。(ps:函数都是自己实现的,但是读取图片信息用的是emgucv自带的函数)-With c# and emgucv achieved between hough transform circle detection and maximum variance and k-means clustering image segmentation, the fu
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一个快速k均值彩色图像的分割算法,运行环境是matlab!-A fast k-means algorithm for color image segmentation, the operating environment is matlab!
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K均值聚类算法,可用于图像分割,算法简单有效-K-means clustering algorithm can be used to image segmentation and it is simple and effective
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在opencv环境下使用fuzzy c means和kmeans算法实现图片像素RGB值聚类,希望对大家有帮助-using fuzzy c means and k-means algorithm to realize the RGB image segmentation in opencv.
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This program illustrates the Fuzzy c-means segmentation of an image.
This program converts an input image into two segments using Fuzzy k-means
algorithm. The output is stored as fuzzysegmented.jpg in the current directory.
This program ca
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基于K-means聚类算法对彩色图象进行分割,聚类的个数可由自己定义.-Based on K- means clustering algorithm for color image segmentation,and the number of clustering can be defined by yourself.
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