文件名称:Kmeansclustering
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Windows] [Visual C] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 2.23mb
- 下载次数：
- 0次
- 提 供 者：
- 王*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
示例程序使用K均值聚类的方法实现了对位图图像的分割即轮廓提取，程序中附带一张位图，可直接打开查看效果、-Sample programs using the K-means clustering methods have been exported to a bitmap image segmentation or contour extraction, the program comes with a digital map, can be directly open the view results
相关搜索： 轮廓提取
(系统自动生成,下载前可以参看下载内容)
下载文件列表
K-means clustering\ChildFrm.cpp
..................\ChildFrm.h
..................\Color.cpp
..................\Debug\ChildFrm.obj
..................\.....\Color.obj
..................\.....\DERSImg.exe
..................\.....\DERSImg.ilk
..................\.....\DERSImg.obj
..................\.....\DERSImg.pch
..................\.....\DERSImg.pdb
..................\.....\DERSImg.res
..................\.....\Dib.obj
..................\.....\Dibapi.obj
..................\.....\ImageDoc.obj
..................\.....\ImageView.obj
..................\.....\KMEAN.obj
..................\.....\MainFrm.obj
..................\.....\StdAfx.obj
..................\.....\vc60.idb
..................\.....\vc60.pdb
..................\DERSImg.aps
..................\DERSImg.clw
..................\DERSImg.cpp
..................\DERSImg.dsp
..................\DERSImg.dsw
..................\DERSImg.h
..................\DERSImg.ncb
..................\DERSImg.opt
..................\DERSImg.plg
..................\DERSImg.rc
..................\DERSImg.reg
..................\Dib.cpp
..................\Dib.h
..................\Dibapi.cpp
..................\Dibapi.h
..................\dlgthreshold.cpp
..................\dlgthreshold.h
..................\ImageDoc.cpp
..................\ImageDoc.h
..................\ImageView.cpp
..................\ImageView.h
..................\KMEAN.cpp
..................\KMEAN.h
..................\MainFrm.cpp
..................\MainFrm.h
..................\ReadMe.txt
..................\res\DERSImg.ico
..................\...\DERSImg.rc2
..................\...\ImageDoc.ico
..................\...\Toolbar.bmp
..................\resource.h
..................\StdAfx.cpp
..................\StdAfx.h
..................\聚类.bmp
..................\Debug
..................\res
K-means clustering
..................\ChildFrm.h
..................\Color.cpp
..................\Debug\ChildFrm.obj
..................\.....\Color.obj
..................\.....\DERSImg.exe
..................\.....\DERSImg.ilk
..................\.....\DERSImg.obj
..................\.....\DERSImg.pch
..................\.....\DERSImg.pdb
..................\.....\DERSImg.res
..................\.....\Dib.obj
..................\.....\Dibapi.obj
..................\.....\ImageDoc.obj
..................\.....\ImageView.obj
..................\.....\KMEAN.obj
..................\.....\MainFrm.obj
..................\.....\StdAfx.obj
..................\.....\vc60.idb
..................\.....\vc60.pdb
..................\DERSImg.aps
..................\DERSImg.clw
..................\DERSImg.cpp
..................\DERSImg.dsp
..................\DERSImg.dsw
..................\DERSImg.h
..................\DERSImg.ncb
..................\DERSImg.opt
..................\DERSImg.plg
..................\DERSImg.rc
..................\DERSImg.reg
..................\Dib.cpp
..................\Dib.h
..................\Dibapi.cpp
..................\Dibapi.h
..................\dlgthreshold.cpp
..................\dlgthreshold.h
..................\ImageDoc.cpp
..................\ImageDoc.h
..................\ImageView.cpp
..................\ImageView.h
..................\KMEAN.cpp
..................\KMEAN.h
..................\MainFrm.cpp
..................\MainFrm.h
..................\ReadMe.txt
..................\res\DERSImg.ico
..................\...\DERSImg.rc2
..................\...\ImageDoc.ico
..................\...\Toolbar.bmp
..................\resource.h
..................\StdAfx.cpp
..................\StdAfx.h
..................\聚类.bmp
..................\Debug
..................\res
K-means clustering