搜索资源列表
KFCMClust529
- 标准的模糊C聚类算法程序,做聚类图像处理的非常有用-the corresponding algorithms are called kernel fuzzy c-means (KFCM) and kernel possibilistic c-means (KPCM) algorithms. And some test results are given to illustrate the advantages of the proposed algorithms over
fcm
- 通过模糊c-均值(FCM)聚类实现图像的分割。-Through the fuzzy c-means (FCM) clustering to achieve image segmentation.
loc_im_MSfilter
- 基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类,即把收敛到同一点的起始点归为一类,然后把这一类的标号赋给这些起始点,同时把包含像素点太少的类去掉。然后,采用阈值化分割的方法对图像进行二值化处理。-Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixe
im_MSfilter
- 基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类,即把收敛到同一点的起始点归为一类,然后把这一类的标号赋给这些起始点,同时把包含像素点太少的类去掉。然后,采用阈值化分割的方法对图像进行二值化处理 -Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixe
c_mean
- 用matlab实现的c均值聚类算法,用于图像分割,分割效果很好-Matlab achieved with c-means clustering algorithm for image segmentation, segmentation well
yansejulei
- 图像颜色聚类分割,实现了图形分割,基于RGB特征并显示出来。-Color image segmentation clustering, to achieve the graphics division, based on the characteristics of RGB and displayed.
C__julei
- 一种非常实用的C均值聚类算法,可以用于数据挖掘、图像分割等领域-A very useful C-means clustering algorithm can be used for data mining, image segmentation and other areas of
k_means
- k-均值聚类法用于各种图像的聚类、分割问题,希望可以对您有利-k-means clustering method for a variety of image clustering, segmentation
GUISUSAN
- 边缘是图像最基本的特征,是图像分割的第一步。经典的边缘检测方法如:Roberts,Sobel,Prewitt,Kirsch,Laplace等方法,基本都是对原始图像中象素的小邻域构造边缘检测算子,进行一阶微分或二阶微分运算,求得梯度最大值或二阶导数的过零点,最后选取适当的阀值提取边界。由于这些算法涉及梯度的运算,因此均存在对噪声敏感、计算量大等缺点。在实践中,发现SUSAN算法只基于对周边象素的灰度比较,完全不涉及梯度的运算,因此其抗噪声能力很强,运算量也比较小。并将SUSAN算法用于多类图像的
FCMandKFCM
- 采用模糊聚类算法和加核模糊聚类算法进行医学图像的分割。采用matlab编程,界面处理较好。 -Using fuzzy clustering algorithm and processing of nuclear fuzzy clustering algorithm for medical image segmentation. Using matlab programming, interface, better handling.
hehanshufcm
- 用Matlab实现基于核函数的C均值聚类图像分割,实验好,好用-Using Matlab implementation of kernel-based C-means clustering image segmentation, experimental is good, easy to use
imgkmeans
- 将K均值算法用于图像分割,输入的是彩色图像,转换为灰度图像进行分割,输出结果为灰度图像.利用灰度做为特征对每个像素进行聚类,由于光照等原因,有时应该属于一个物体的像素,其灰度值也会有很大的差别,可能导致对该像素的聚类发生错误.在分割结果中,该物体表面会出现一些不同于其它像素的噪声点,因此,算法的最后,对结果进行一次中值滤波,以消除噪声,达到平滑图像的作用-The K means algorithm for image segmentation, the input is a color imag
ImageFusion
- 数字图像的加噪、去噪、聚类分析和融合的Matlab实现。-Plus digital image noise, denoising, clustering analysis, and integration of Matlab implementation.
Kmeans_grayimage
- 简单的灰度图像的K均值聚类分割,Matlab实现-gray image segmentation using K-means clustering by matlab.
NcutImage_7_AMD64
- 经典的C-CUT算法的MATLAB实现 由 Jianbo Shi创立。是聚类算法和图像处理的经典算法。-The classic C-CUT algorithm of the MATLAB realization founded by Jianbo Shi.
kmean2
- 本程序用k-均值聚类的方法实现图像二值化-This procedure using k means to achieve image binarization
imadeedgesegmentation
- 本程序实现了采用聚类法对图像进行分割,给出了图像分割前后的直方图,程序内有详细的程序说明和例图像-This program was realized using clustering method for image segmentation is presented, and the histogram image segmentation, procedure in detail program
ZPclustering
- 用于图像分割的自调整普聚类算法,可实现大多数图像的无监督分割-Self-tunning spectral clustering for image segmentation
tuxiangfenge(Matlab)
- 有图像分割的各种算法:分水岭 最大类间 最大熵法等等源程序-With image segmentation algorithms: the watershed between the largest class of maximum entropy source, etc.
kfcm
- 基于核的FCM,可以用于聚类或者图像分割,但运行速度不是很快 自己不知道如何优化-Kernel-based FCM, can be used for clustering or image segmentation, but the speed is not fast they do not know how to optimize