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一种基于前景与背景划分的区域图像检索方法及实现
引用本文:朱远清,李才伟.一种基于前景与背景划分的区域图像检索方法及实现[J].中国图象图形学报,2007,12(2):234-238.
作者姓名:朱远清  李才伟
作者单位:中山大学计算机科学系 广州510275
摘    要:区域图像检索(RBIR)是基于内容图像检索(CBIR)的一个分支,它以图像分割为基础,通过图像局部视觉特征的相似性进行图像检索。由于准确的图像分割技术尚不成熟,区域图像检索性能容易受到冗余分割和错误分割的影响。为了降低RBIR中图像分割的影响,提出了一种基于前景和背景划分的区域图像检索方法。该方法通过规则分块、图像分类和有效区域定位来得到图像分割区域,然后应用中心对象提取算法(COEA)获得图像主体对象,最后提取颜色和纹理特征进行相似度匹配。实现了一个基于上述方法的RBIR系统ObFind,实验结果表明该方法不仅具有与SIMPLIcity相当的检索性能,而且计算复杂度更低。

关 键 词:区域图像检索  前景划分  图像分割
文章编号:1006-8961(2007)02-0234-05
修稿时间:2006-10-13

A Method and Implementation for Region-based Image Retrieval Using Partition of Foreground and Background
ZHU Yuan-qing,LI Cai-wei and ZHU Yuan-qing,LI Cai-wei.A Method and Implementation for Region-based Image Retrieval Using Partition of Foreground and Background[J].Journal of Image and Graphics,2007,12(2):234-238.
Authors:ZHU Yuan-qing  LI Cai-wei and ZHU Yuan-qing  LI Cai-wei
Affiliation:Department of Computer Science, Sun Yat-sen University, Guangzhou 510275
Abstract:Region-based Image Retrieval(RBIR) is a sub-branch of Contentbased Image Retrieval(CBIR).It employs image segmentation to extract local visual feature and retrieves images by similarity matching.However,as precise image segmentation is still immature,the performance of RBIR systems is subject to redundant and inaccurate segmentation.In order to reduce adverse effect of image segmentation in RBIR,a new method based on partition of foreground and background is proposed.In the method,image segmentation regions are obtained by applying regular block,classification and valid region location.And the principal object is extracted using the Central Object Extraction Algorithm(COEA).Then images are retrieved by similarity matching based on extracted color and texture feature.In the paper,a RBIR system named ObFind is implemented according to the proposed method.The experimental results show that the proposed method not only has comparable performance to SIMPLIcity but also reduces computation complexity.
Keywords:region-based image retrieval  foreground partition  image segmentation
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