搜索资源列表
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主要实现对于图像内容的K均值聚类算法，以达到分割的目的-main image content for the K-means clustering algorithm to achieve the purpose of segmentation
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彩色图像分割程序，采用k-means算法，用c++语言编写。 ,Color image segmentation procedures, the use of k-means algorithm, with c++ languages.
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colour image segmentation k means algorithm
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这是K均值聚类算法 对图像颜色进行聚类 然后对图像分割源代码-This is the K-means clustering algorithm for image clustering and then color image segmentation source code
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示例程序使用K均值聚类的方法实现了对位图图像的分割即轮廓提取，程序中附带一张位图，可直接打开查看效果、-Sample programs using the K-means clustering methods have been exported to a bitmap image segmentation or contour extraction, the program comes with a digital map, can be directly open the view resu
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基于K-均值聚类算法的中药叶片显微图像分割-K-means clustering algorithm based on Chinese medicine leaves Image Segmentation
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基于C语言的K-means聚类分析，可完成图像分割-C language-based K-means cluster analysis of image segmentation
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K均值用于图像分割的Matlab程序，直接可用-K means Matlab for image segmentation process, directly available
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WINDOWS操作系统下MATLAB图像处理工具箱，非常好用-Matlab demo-Image processing toolbox
- Texture Segmentation Using Texture Filte
(entropyfilt)
- color-Based Segmentation Using K-Means Clustering
Vgg-matlab
Zisserman: Texture Classification: Are Filt
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用MATLAB编写的K均值聚类用于图像分割-Written by K-means clustering MATLAB for image segmentation
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image segmentation of color images using k means
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该程序用于分割图像的不同区域，其中采用了K-means算法。-image segmentation for different regions
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本项目是居于K均值聚类的思想，对灰度图像进行分割。-This project is the idea of living in the K-means clustering, the gray scale image segmentation.
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基于K均值聚类的图像分割，灰度图像分割案例，真彩图像分割案例-K-means clustering-based image segmentation, image segmentation case, the true color image segmentation case
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一种应用K均值算法应用于图像分割中的技术-An application k-means algorithm is applied to image segmentation of technology
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基于色彩空间，使用K均值聚类算法对图像进行分割。目标是自动使用L*a*b色彩空间和k均值聚类算法实现图像分割。-Based on the color space, using the K-means clustering algorithm for image segmentation. The goal is to automatically use the L* a* b* color space and k-means clustering algorithm to achieve ima
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贝叶斯分类程序，用于图像的分割，二值化等，是模式识别中的一种基本分类方法。
k均值聚类，神经网络-Bayesian classification procedures for image segmentation, binarization is a basic classification in pattern recognition. k-means clustering, neural networks
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完全用C++写得k-means算法实现图像分割源代码，逐个字节读取图像，-Completely with C++ write the k-means algorithm to achieve image segmentation source code, one by one byte to read the image,
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K均值聚类算法 对图像颜色进行行聚类 然后对图像分割可直接使用。
-K-means clustering algorithm for image color line clustering and image segmentation can be used directly.
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kmeans image segmentation
Input:
ima: grey color image
k: Number of classes
Output:
mu: vector of class means
mask: clasification image mask
-kmeans image segmentation
Input:
ima: grey color image
k: Numbe
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