Description: 基于OpenCV的K-均值算法,用于聚类分析,如图象的颜色聚类,生成相关的颜色表等.-the K-means algorithm for clustering analysis, such as image color clustering, Formation of color, and so on. Platform: |
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Author:guolijun |
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Description: 基于OpenCV的K-均值算法,用于聚类分析,如图象的颜色聚类,生成相关的颜色表等.-the K-means algorithm for clustering analysis, such as image color clustering, Formation of color, and so on. Platform: |
Size: 2048 |
Author:guolijun |
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Description: 基于Opencv实现的k-means聚类图像分割算法，可自定义聚类个数，根据像素点的位置和颜色进行聚类-Opencv based on the realization of the k-means clustering image segmentation algorithm, the number of clustering can be customized, according to pixel location and color clustering Platform: |
Size: 3536896 |
Author:drowning |
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Description: 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 planning svm simple algorithm vc2008-based image matching (multi-project structure) local search based on the K-means clustering algorithm three-dimensional matching of the ICP algorithm visual tracking of the condensation algorithm Platform: |
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Author:zhezhe |
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Description: 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 OpenCV. Platform: |
Size: 2835456 |
Author:chenwenlue |
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Description: 使用k-means算法对一副RGB色彩空间的图像作简单的聚类。根据命令行提示输入聚类的大小K，程序自动计算每一个像素点的归属并着色该点为该类的色彩均值。工程运行于VS2008环境，需要OpenCV支持。Debug目下exe文件可以直接双击运行查看结果。-Using k-means algorithm on an RGB color space images to make a simple clustering. According to the command prompt enter the size of clusters K, the program automatically calculates the ownership of each pixel and color of the color point average for the class. This project runs under VS2008 with OpenCV. Double click the exe file under Debug folder to check the final result. Platform: |
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Author: |
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Description: 图像场景分类的bow模型opencv源代码，采用k-means聚类构造单词，采用支持向量机的svm分类器。-Image scene classification bow model opencv source code, using k-means clustering structure of words, using support vector machine svm classifier. Platform: |
Size: 10240 |
Author:李翔 |
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Description: 视频图像的人群密度检测，多种人群密度场景下人群计数算法：
算法功能:建立图像特征和图像人数的数学关系
算法输入:训练样本图像1,2…K
算法输出:模型估计参数 ，参考图像
算法流程：1)对训练样本图像进行分块处理(算法1.1)；
2)通过算法1.2，计算训练样本各个对应分块的ALBP特征归一化，再用K-means算法(可使用opencv等算法库实现，不再描述其算法)，将图像块分成k(k<K)类，获取k(k<K)个聚类中心，即为参考图像；
3)对分块的图像进行与参考图像进行匹配。使用算法1.2求取ALBP特征，并求取其相似度 ，将相似性集合作为新特征并形成一个归一化的新特征 。
4)按照行人面积占图像块面积的比例，以60 为分界，分布采用径向基核函数 和线性核函数 。K(xi,x)建立图像特征和图像人数的SVR(支持向量回归机)模型可使用opencv中的SVM或libsvm，输出模型估计参数 。
-Population density detection of video images, a variety of crowd density scenes crowd counting algorithm:
Algorithm functions: a mathematical relation between the image features and the number of images
Algorithm Input: training sample image 1,2 ... K
Algorithm output: model estimation parameters, reference image
Algorithmic process: 1) the training sample image into blocks (algorithm 1.1)
2) by 1.2 algorithm to calculate the corresponding training samples of each block ALBP features normalized, then K-means algorithm (algorithm can be used opencv library implementation, no longer describe the algorithm), the image block is divided into k (k <K) class, gets k (k <K) clustering centers, namely the reference image
3) conduct of image block matching with the reference image. 1.2 ALBP characterized using an algorithm to strike, and strike the similarity, the similarity of a set of new features and forming a normalized new features.
4) pedestrian area accounted for in Platform: |
Size: 4759552 |
Author:徐云华 |
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Description: 用K-means算法将点进行聚类，点以结构体的形式表示，opencv+vs2010跑通。-By K-means clustering algorithm point, the point structure in the form of representation, opencv+ vs2010 run through. Platform: |
Size: 2462720 |
Author:张娇 |
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Description: 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 target detection and pattern recognition. Image segmentation is an important image analysis technique in image processing. The basic method of image segmentation is to segment the gray image, the luminance image processing, simple and fast. This paper introduces the traditional segmentation of image segmentation and K- means clustering algorithm, and then use the OpenCV function to achieve the basic functions, and introduces the segmentation of OpenCV in the relevant image. Platform: |
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Author:潇枫 |
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Description: K均值聚类算法
属于模式识别的一种基本算法 在此没有与opencv关联-K-means clustering algorithm
A basic pattern recognition algorithm is not associated with this opencv Platform: |
Size: 1024 |
Author:左颜汐 |
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Search - k means clustering OpenCV