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kmeans算法。opencv上面聚类算法的例子
- kmeans算法。opencv上面聚类算法的例子，是一个很好的学习程序。-kmeans algorithm. A good example for learning kmeans.
color-cluster
- 基于opencv的图像颜色聚类算法。聚类精度较高，但颜色数目需要输入。-Opencv image-based color clustering algorithm. Clustering high accuracy, but the number of colors required to enter.
kmeans-cluster-with-openCV
- openCV平台下kmeans聚类的实现-Kmeans clustering implementation with OpenCV
opencv
- 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.
KmeansaFCM
- 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.
optical
- opencv写的基于光流法的运动人流分类，能够实现读取视频，实现金字塔光流法和HS光流法，最后对流动人群进行有效的聚类。-Opencv writing movement flow classification based on optical flow method, read the video, can be implemented to realize pyramid optical flow method and the HS optical flow method, finally,
1K_means
- 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.
KMkeen
- 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
MFCVIDEO
- 基于opencv的运动人流分类，采用了帧差法、DBSCAN聚类算法实现-Based on opencv motion flow classification, using the frame difference, DBSCAN clustering algorithm
K均值聚类在基于OpenCV的图像分割中的应用
- 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
divnted-the
- DBSCAN是一个基于密度的聚类算法,改算法将具有足够高度的区域划分为簇(DBSCAN is a density based clustering algorithm, the algorithm will have enough height area is divided into clusters)
epbxvcf
- 关于聚类问题的matlab程序以及其中函数的说明 推荐一下(Matlab, and the function about clustering problem recommend)
Otsu方法
- opencv做的otsu方法,一、Otsu算法原理 Otsu算法（大津法或最大类间方差法）使用的是聚类的思想，把图像的灰度数按灰度级分成2个部分，使得两个部分之间的灰度值差异最大，每个部分之间的灰度差异最小，通过方差的计算来寻找一个合适的灰度级别来划分。 所以可以在二值化的时候采用otsu算法来自动选取阈值进行二值化。otsu算法被认为是图像分割中阈值选取的最佳算法，计算简单，不受图像亮度和对比度的影响。因此，使类间方差最大的分割意味着错分概率最小。 设t为设定的阈值。(otsu made
kmeans
- 基于windows平台和k-聚类算法，对平面点集进行聚类(Based on the windows platform and the k- clustering algorithm, the plane point set is clustered)