搜索资源列表
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利用hsv颜色模板对图像进行分割。在OpenCV环境下开发完成。-Hsv color template using the image segmentation. Environment developed in OpenCV.
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基于mean—shift的彩色图像分割,包含了采用mean shift进行彩色图像分割的源代码和2篇相关的论文。-Mean-shift based color image segmentation, including the use of mean shift to color image segmentation of the source code and two related papers.
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利用k-means算法进行图像分割,效果较好-Using k-means algorithm for image segmentation is better
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matlab写的ostu最佳阈值图像分割- ostu optimal image segmentation write with matlab
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一种新型的图像分割技术,是基于Ncut的改进-A new image segmentation technique is based on the improvement Ncut
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纹理图像分割matlab程序,附带测试纹理图像图像,另外还有一篇高质量相关英文论文和一篇中文论文,供研究纹理分割的同学学习。-Texture image segmentation matlab, the supplementary test texture image image, in addition to a high quality related English papers and a Chinese paper, for research students texture segm
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用matlab实现了FCM图像分割,分割效果较好。有说明-Matlab achieved using FCM image segmentation, segmentation better. Described
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C#实现图像分割,包括图片示例。实现了各种图像分割的算法-C# to write image segmentation system with case images
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四叉树分解算法对RGB彩色图像进行分割,MATLAB代码,包括实验图片-Quad-tree decomposition algorithm RGB color image segmentation, MATLAB code, including test images
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图像分割,这是基于脑部的MRI图像的分割,其中有多个m文件-Segmentation, which is based on the MRI brain image segmentation, in which there are several m files
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区域生长算法,用于图像分割。
运行RunGrow.m
修改文件名即可。-Region growing algorithm for image segmentation. Run RunGrow.m modify the file name.
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实现ICM算法(条件迭代模型)对于灰度图像的分割-Achieve ICM algorithm (iterative model conditions) for the gray-scale image segmentation
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基于Snake模型的图像分割技术是近年来图像处理领域的研究热点之一。Snake模型承载上层先验知识并融合
了图像的底层特征,针对医学图像的特殊性,能有效地应用于医学图像的分割中。本文对各种基于Snake模型的改进算法和
进化模型进行了研究,并重点梳理了最新的研究成果,以利于把握基于Snake模型的医学图像分割方法的脉络和发展方向-Snake model based image segmentation image processing technology in recent years
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it is about snake algorithm which is used in medical image segmentation.
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这个代码是文章Efficient Graph-Based Image Segmentation的实现,结合了vs2008和opencv,该算法进行分割,速度很快,效果不错。-The source code is an implementation of the paper: Efficient Graph-Based Image Segmentation. VS2008 and Opencv are combined in the implementation process.
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基于K均值算法和互信息熵差的算法,可以有效地确定分类数,从而该算法对医学图像进行自动优化分割。-K means algorithm based on entropy and mutual information algorithms, can effectively determine the classification number, so that the algorithm for automatic optimization of medical image segmentation.
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快速K均值聚类图像分割算法源代码,能很好的实现图像的分割处理-Fast K-means clustering algorithm for image segmentation source code, can achieve very good to deal with image segmentation
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自组织神经分割算法,实现"Woman.bmp"的图像分割。-Self-organizing neural segmentation
Achieve "Woman.BMP" image segmentation
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基于MEAN SHIFT算法的图像分割程序-MEAN SHIFT algorithm based on image segmentation procedure
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利用EM算法进行的彩色图像分割,利用EM算法进行的彩色图像分割-The use of EM algorithm for color image segmentation
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