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基于颜色-空间特征的图像检索
引用本文:王涛,胡事民,孙家广.基于颜色-空间特征的图像检索[J].软件学报,2002,13(10):2031-2036.
作者姓名:王涛  胡事民  孙家广
作者单位:清华大学,计算机科学与技术系,北京,100084
基金项目:国家自然科学基金资助项目(69902004);国家重点基础研究发展规划973资助项目(G1998030600)
摘    要:虽然基于颜色直方图特征的图像检索方法简单、高效,但却丢失了颜色的空间分布信息.提出了一种基于颜色-空间特征的图像检索方法.该方法将图像内容看成由若干对象组成的集合,首先利用图像分割得到主要对象,然后根据对象的颜色、位置和形状特征计算图像间内容的相似度,再进行检索.实验结果表明,当图像中有明显的物体时,该方法与颜色直方图相比,能够更加准确和高效地查找出用户所需内容的图像,明显地提高了检索精度.

关 键 词:基于内容的图像检索(CBIR)    HSV颜色模型  图像分割  图像相似度
收稿时间:2000/12/12 0:00:00
修稿时间:3/9/2001 12:00:00 AM

Image Retrieval Based on Color-Spatial Feature
WANG Tao,HU Shi-min and SUN Jia-guang.Image Retrieval Based on Color-Spatial Feature[J].Journal of Software,2002,13(10):2031-2036.
Authors:WANG Tao  HU Shi-min and SUN Jia-guang
Abstract:The color histogram based image retrieval method is simple and efficient but losing the spatial distribution information of the color. In this paper, a color-space feature based image retrieval method is presented. The content of one image is looked as the aggregation of some main objects, which can be obtained by image segmentation. The total similarity between two images is computed according to these main objects?color, location and shape features and then retrieval there images. The experimental results show that the method is more accurate and efficient in retrieving the user interested images than color histogram method when there are obvious objects in the image.
Keywords:content based image retrieval (CBIR)  HSV color model  image segmentation  image similarity
本文献已被 CNKI 维普 万方数据 等数据库收录!
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