| 基于多变量类别自适应的图像分割算法 |
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| 引用本文： | 常兴治,高立群. 基于多变量类别自适应的图像分割算法[J]. 计算机辅助设计与图形学学报, 2008, 20(10) |
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| 作者姓名： | 常兴治 高立群 |
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| 作者单位： | 1. 中国科学院青岛生物能源与过程研究所,青岛,266071;东北大学信息科学与工程学院,沈阳,110004
2. 东北大学信息科学与工程学院,沈阳,110004 |
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| 基金项目： | 公安部科研项目，黑龙江省自然科学基金 |
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| 摘 要： | 提出一种根据分割要求自动配置区域平滑性的图像分割算法.通过对现有的类别自适应空间变量混合模型进行改进,修改模型算法中Markov随机场的势函数部分,在判断分割区域环节时引入了像素的色彩或灰度信息,使改进后算法的稳定性有明显提升;同时增加了像素强度系数α以及算法的灵活性,提高了其实用价值.最后在MIT及Berkeley的分割测试图片上进行仿真实验,证明了该算法的有效性.
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| 关 键 词： | Markov随机场 图像分割 EM聚类 |
Image Segmentation Based on Class Adaptive Spatially Variant Mixture Model |
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| Chang Xingzhi,Gao Liqun. Image Segmentation Based on Class Adaptive Spatially Variant Mixture Model[J]. Journal of Computer-Aided Design & Computer Graphics, 2008, 20(10) |
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| Authors: | Chang Xingzhi Gao Liqun |
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| Affiliation: | Chang Xingzhi 1,2) Gao Liqun 2) 1)(Qingdao Institute of BioEnergy , Bioprocess Technology,Chinese Academy of Sciences,Qingdao 266071) 2)(College of Information Science , Engineering,Northeastern University,Shenyang 110004) |
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| Abstract: | This paper proposes an image segmentation method which allocates regional smoothness automatically according to the requirements.The method improves existing class adaptive spatially variant mixture model based on revising the potential function in Markov random field and introducing colorful or grey feature information into the assessment of segmentation regions.As a result,the stability by the revised method is improved significantly.Meanwhile,the added pixel strength coefficients to the method increase i... |
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| Keywords: | Markov random field image segmentation EM clustering |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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