| 多分类器融合的快速高维特征聚类图像分割 |
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| 引用本文： | 黄荣顺,吴宏刚,刘思远. 多分类器融合的快速高维特征聚类图像分割[J]. 电讯技术, 2010, 50(3): 12-17. DOI: 10.3969/j.issn.1001-893x.2010.03.003 |
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| 作者姓名： | 黄荣顺 吴宏刚 刘思远 |
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| 作者单位： | 中国民用航空局第二研究所,成都,610041;中兴通讯成都研究所,成都,610041 |
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| 基金项目： | 国家自然科学基金重点资助项目 |
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| 摘 要： | 提出一种多分类器融合的快速高维特征聚类图像分割方法,将图像高维特征数据的分类分解为基于灰度(颜色)特征的最佳模糊分类以及基于空域约束的统计分类等多个低维特征数据的分类.通过多分类器融合的方法将不同分类器得到的分类结果进行优化整合,得到最后的分类结果.实验证明:与其它图像分类算法相比,该方法拥有更好的分割性能并大大提高了计算速度,最大限度地保证了分割算法计算的简单有效性.
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| 关 键 词： | 图像分割 高维特征聚类 多分类器融合 |
Image Segmentation Based on Fast High Dimensional Characteristic Clustering Using Combination of Classifiers |
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| HUANG Rong-shun,WU Hong-gang and LIU Si-yuan. Image Segmentation Based on Fast High Dimensional Characteristic Clustering Using Combination of Classifiers[J]. Telecommunication Engineering, 2010, 50(3): 12-17. DOI: 10.3969/j.issn.1001-893x.2010.03.003 |
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| Authors: | HUANG Rong-shun WU Hong-gang LIU Si-yuan |
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| Affiliation: | The Second Research Institute of CAAC, Chengdu 610041, China;The Second Research Institute of CAAC, Chengdu 610041, China;Institute of Chengdu, ZTE Corporation, Chengdu 610041, China |
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| Abstract: | A new image segmentation algorithm is proposed which is based on fast high dimensional characteristic clustering using combination of classifiers.In the algorithm, the clustering of high dimensional characteristic data is divided into optimal fuzzy classifying of grayscale (color) and statistical classifying of spatial constraint information. The classification results of the two different classifiers are integrated to obtain the final image segmentation result using combination of classifiers.Experiment result proves the good performance and computation simplicity of the algorithm. |
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| Keywords: | image segmentation high dimensional characteristic clustering combination of classifiers |
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