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用openCV提取图片的象素值，用聚类进行分割，找出各个聚类的中心点，聚类个数是动态决定的，可重新设置个数最大上限。-OpenCV extract images using pixel value segmentation by clustering to identify the center of each cluster, clustering is a dynamic number of decisions can be re-set the upper limit of the num
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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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C 调用opencv，边缘检测，图像分割，插值拟合，聚类变换，图像修改-C call opencv, edge detection, image segmentation, interpolation fitting, clustering transform, image modification
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用openCV提取图片的象素值，用聚类进行分割，找出各个聚类的中心点，聚类个数是动态决定的，可重新设置个数最大上限。-OpenCV extract images using pixel value segmentation by clustering to identify the center of each cluster, clustering is a dynamic number of decisions can be re-set the upper limit of the num
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基于人类视觉将图像分割成若干个有意义的区域是目标检测和模式识别的基础。图像分割属于图像处理中一种重要的图像分析技术。图像分割的基本方法是对灰度图像分割，处理图像的亮度分量，简单快速。本论文介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。-Based on the human visual image is segmented into several meaningful regions is the basis for
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this is clustering based on image segmentation in python and opencv.
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介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。(This paper introduces the segmentation of traditional image segmentation and K- mean clustering algorithm, then uses OpenCV function to implement it, and introduces the basic functions of
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