| 基于语义的图像物体提取的新方法 |
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| 引用本文： | 余卫宇,曹燕,余英林.基于语义的图像物体提取的新方法[J].微计算机信息,2007,23(21):211-213. |
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| 作者姓名： | 余卫宇 曹燕 余英林 |
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| 作者单位： | 510640,广州,华南理工大学,电子与信息学院 |
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| 基金项目： | 国家自然科学基金;广东省自然科学基金 |
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| 摘 要： | 在图像语义研究中,提取图像中的语义物体或区域是重要的.本文首先对图像预处理,通过颜色空间的转换,在空间对图像进行K-均值分类,提取出具有语义性质的物体和区域.实验结果表明该方法是可行的,而且很有效的.
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| 关 键 词： | 彩色分类 K-均值算法 语义信息 物体提取 |
| 文章编号： | 1008-0570（2007）07-3-0211-03 |
| 修稿时间： | 2007-06-032007-07-05 |
A Novel Extracting Image Semantic Objects Based on Semantic |
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| YU WEIYU,CAO YAN,YU YINGLIN.A Novel Extracting Image Semantic Objects Based on Semantic[J].Control & Automation,2007,23(21):211-213. |
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| Authors: | YU WEIYU CAO YAN YU YINGLIN |
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| Affiliation: | Institute of Electronic and Control, South China Univ. of Tech, Guangzhou, China 510640 |
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| Abstract: | The color classification process requires to partition a color image into uniform color regions. It is very important that extract interesting region or object in image semantic analysis. In this paper we propose an approach to extract semantic region based on color feature. First, we translate RGB space into Lab space. Second, we use the k-means algorithm solve clustering problem. In the end, we extract semantic object in terms of color information. Experimental results show that the color clustering give superior results in increases in cluster effectiveness. |
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| Keywords: | Color classification K-means clustering Semantic Information Object extraction |
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