搜索资源列表
LocalOstu
- 基于opencv的otsu阈值分割,根据最大类间方差原理,进行全局图像分类-Opencv based on the Otsu threshold segmentation, in accordance with the principle of maximum between-cluster variance for the overall image classification
K_MeansSeg
- 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
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.
k-means
- opencv k-meas 聚类分割，将图片分为2部分，主要针对道路特征-opencv ， cluster
kmeans-cluster-with-openCV
- openCV平台下kmeans聚类的实现-Kmeans clustering implementation with OpenCV
k-means
- k—均值算法opencv代码实现。 k-Means 算法是一种 cluster analysis 的算法，其主要是来计算数据聚集的算法，主要通过不断地取离种子点最近均值的算法。
kMeansProjectiveClustering
- Kmeans in opencv to cluster image.
1EMalgorithm
- 利用期望最大化聚类算法，从txt文件中读如200+个点的坐标，并将这些点尽心聚类。开发环境为opencv+vs2010-Expectation Maximization clustering algorithm, txt file read coordinates 200+ points, and these points dedicated cluster. opencv+ vs2010
craw-specification-cluster
- 用Matlab编写的小波去噪,对初学者有所帮助,还可以的(Matlab prepared by the wavelet denoising, some help for beginners, can also)