搜索资源列表
clustering-system
- 本程序的最终目的是形成一套标准的用于聚类、可扩展的工具。包括的内容有1. 聚类算法：Kmeans和Kmedoid算法、FCMclust, GKclust, GGclust算法 2. 评估分类原型：程序可以在二维图像上绘制出聚类的结果 3. 验证：程序给每一个算法提供验证机制，每个聚类算法会统计Partition Coefficient (PC), Classification Entropy (CE), Partition Index (SC), Separation Index (S), Xi
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.
kind
- candy边缘检测，彩色图像的边缘检测，K均值聚类，sobel边缘检测（C）其他是matlab程序-candy edge detection, color image edge detection, K-means clustering, sobel edge detection (C) the other is a matlab program
HCI
- 功能：求两幅图像的相似度，进而用于图像检索 尽管一幅彩色图像包含成千上万种颜色,但在多数情况下,图像中少数几种颜色就涵盖了图像中的大多数的象素颜色。这些颜色被称为主色。一些研究表明:使用主色一般不会降低颜色匹配效果。因此考虑一种次优可行的基于聚类颜色特征的相似度计算方法。 -Function: Find the similarity of two images, and then used for image retrieval although a color image con
FCM-Image-Cluster
- 使用FCM和HCM聚类算法对彩色图像进行聚类分割。-Use Fcm and HCM Method to cluster color image.
聚类算法
- 基于谱聚类和Kmeans算法的聚类分析，有效地将图像进行分块聚类MATLAB代码
K均值聚类
- K均值聚类算法图像分割，最传统的一种分割方法(K mean clustering segmentation)
k_means
- 用kmeans算法处理资源3号卫星图像，用欧式距离来计算聚类中心，在用前后两次聚类之间的误差来决定迭代次数(Kmeans algorithm is used to deal with the resource 3 satellite image, and the Euclidean distance is used to calculate the clustering center. The number of iterations is determined by the error bet
MRF-ICM 也是先聚类再算的 里面有论文
- 利用马尔科夫随机场对图像进行语义分割，通过ICm求解参数，可以运行，对初学者有较好的借鉴作用(Using Markov random field to semantic segmentation of images, through ICm solution parameters, can run, for beginners have a good reference)
ZPclustering
- 实现点的聚类，并用做图像分割，来源是文章：Self-Tuning Spectral Clustering (作者: Lihi Zelnik-Manor, Pietro Perona )(point clustering and image segmentation, algorithm is from paper:Self-Tuning Spectral Clustering(author: Lihi Zelnik-Manor, Pietro Perona ))
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
kfcm
- 实现了KFCM算法，对模糊图像进行聚类分析，效果良好(The KFCM algorithm is implemented)
5
- 5基于快速谱聚类的图像分割算法 5 image segmentation algorithm based on fast spectral clustering(5 image segmentation algorithm based on fast spectral clustering)
FLICM
- 通过改进FCM聚类，编写了FLICM聚类，实现图像的聚类分割。(Implementation of FLICM clustering image segmentation)
k-means-image-segmentation-master
- k-means 聚类和分割的图像处理方法(k-means and segement image process)
kmeans
- 对数据和图像进行聚类分析，k-means聚类方法多应用于模式识别，人工智能，机器学习等方面(Clustering analysis of data and images, K-means clustering method should be used in pattern recognition, artificial intelligence, machine learning and so on)
Experiment Three
- matlab的聚类算法实现图像分割,效果很好(Image segmentation by clustering in matlab)
Colors_src
- 图像在读取颜色时，参数较多，处理过程需耗费大量时间，因此通过八叉树颜色聚类算法，提取图像的主色，利于后续的图像处理。(When the color is read, there are many parameters, and the processing process takes a lot of time. Therefore, octree color clustering algorithm is used to extract the main color of the image,
ncut
- ncut在图像分割中的应用及实现（基于谱聚类的理论）(Application and implementation of NCUT in image segmentation)
k-means
- 实现k均值聚类算法，可以使用彩色图像，通过随机初始化聚类中心，完成聚类(The K-means clustering algorithm can use color images to initialize cluster centers randomly and accomplish clustering.)