搜索资源列表
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.)
FCM
- 模糊C均值(FCM)聚类算法分割图像，该算法可以进行图像的分割(Fuzzy C-Means (FCM) clustering algorithm to segment images, which can be used for image segmentation)
K-means图像识别
- 利用K-means对图像进行聚类，识别。您可以设置参数达到更好的识别效果(Using K-means to cluster and identify images.You can set parameters to achieve better recognition results)
FCM
- 利用模糊C聚类（FCM）的方法对彩色图像进行分割，期中可以用不通的特征向量来表征图像的特征(The method of fuzzy C clustering (FCM) is used to segment the color image. In the period of time, the feature vectors can be used to characterize the features of the image.)
GMM
- 实现了EM算法对高斯混合模型进行聚类，并将聚类结果用图像展示出来，希望对混合模型的朋友有用。(The EM algorithm is implemented to cluster the Gauss mixture model, and the clustering results are displayed with images, hoping to be useful to friends of the mixed models.)