计算机工程Issue(11)：229-232,254,5.DOI:10.3969/j.issn.1000-3428.2014.11.045
一种基于区域综合特征的图像检索算法
An Image Retrieval Algorithm Based on Region Integrating Features
王小龙 1沈新宁 1杜建洪1
作者信息
- 1. 复旦大学信息科学与工程学院，上海200433
- 折叠
摘要
Abstract
This paper presents a novel Region-based Image Retrieval ( RBIR ) method to reduce the semantic gap between low-level visual feature and high-level semantic of images in the content-based Image retrieval area. K-means clustering algorithm is used in the LUV color space for image segmentation. The color and shape feature in each region as well as the region auto-correlation feature are extracted as the integrating features of each region. And this paper defines a new Quadratic Distance Similarity Measure( QDSM) to calculate the similarity between different images. Experimental results show that the novel RBIR method using integrating features increases the retrieval performance by 12% ~47 . 8%compared with the traditional methods under Average Normalized Modified Retrieval Rank( ANMRR) metric.关键词
基于区域的图像检索/语义鸿沟/区域自相关特征/图像分割/二次型距离相似性度量/平均归一化修正检索等级Key words
Region-based Image Retrieval( RBIR)/semantic gap/region auto-correlation feature/image segmentation/Quadratic Distance Similarity Measure( QDSM)/Average Normalized Modified Retrieval Rank( ANMRR)分类
信息技术与安全科学引用本文复制引用
王小龙,沈新宁,杜建洪..一种基于区域综合特征的图像检索算法[J].计算机工程,2014,(11):229-232,254,5.
