文件名称:Ibasedoncolorn

  • 所属分类:
  • Windows编程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 1.73mb
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  • 0次
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为了提高非结构化道路识别算法的有效性,提出了一种道路分割的新方法,建立了道路区域域和非道路区域混合高斯彩色模型,根据像素隶属于彩色模型的概率进行基于彩色信息道路 -

-A road split in order to improve the effectiveness of unstructured road recognition algorithm is proposed to establish a road regional domain and non-road area Gaussian mixture color model based on the probability of the pixels belonging to a color model based on color information of the road-
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下载文件列表

Ibasedoncolorn\35738639colorseg\code\angitest.m

..............\................\....\calculatePXTheta.m

..............\................\....\calculateQ.m

..............\................\....\clusterMerge.m

..............\................\....\clusters.mat

..............\................\....\convProd.m

..............\................\....\createPyramid.m

..............\................\....\distances.m

..............\................\....\formCoreClusters.m

..............\................\....\hist\CVS\Entries

..............\................\....\....\...\Repository

..............\................\....\....\...\Root

..............\................\....\....\hist5hel.c

..............\................\....\....\histmulti5.m

..............\................\....\....\README

..............\................\....\images\angkorwat.jpg

..............\................\....\......\angkorwat2.jpg

..............\................\....\......\bagofgrain.jpg

..............\................\....\......\bagofgrain2.jpg

..............\................\....\......\beans.jpg

..............\................\....\......\berries.jpg

..............\................\....\......\buildings.jpg

..............\................\....\......\buildings2.jpg

..............\................\....\......\corn.jpg

..............\................\....\......\corn2.jpg

..............\................\....\......\CVS\Entries

..............\................\....\......\...\Repository

..............\................\....\......\...\Root

..............\................\....\......\easyim1.jpg

..............\................\....\......\easyim2.jpg

..............\................\....\......\flowers.jpg

..............\................\....\......\model.jpg

..............\................\....\......\patchofgrass.jpg

..............\................\....\......\patchofgrass2.jpg

..............\................\....\......\redflowers.jpg

..............\................\....\......\redflowers2.jpg

..............\................\....\......\starfish.jpg

..............\................\....\......\starfish2.jpg

..............\................\....\......\testim1.jpg

..............\................\....\......\testim2.jpg

..............\................\....\......\Thumbs.db

..............\................\....\......\water.jpg

..............\................\....\......\weave.jpg

..............\................\....\......\wolfie.jpg

..............\................\....\jefftest.m

..............\................\....\kclassify.m

..............\................\....\kmeansClusters.m

..............\................\....\patternDictionary.mat

..............\................\....\preprocess.m

..............\................\....\segment.m

..............\................\....\showClusters.m

..............\................\....\showPyramid.m

..............\................\....\sqdist.m

..............\................\....\statsCluster.m

..............\................\....\test1.m

..............\35738639colorseg.zip

..............\................\code\hist\CVS

..............\................\....\images\CVS

..............\................\....\hist

..............\................\....\images

..............\................\code

..............\35738639colorseg

Ibasedoncolorn

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