张宏伟

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:数学科学学院

电子邮箱:hwzhang@dlut.edu.cn

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Global Correlation Descriptor: A novel image representation for image retrieval

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论文类型:期刊论文

第一作者:Feng, Lin

通讯作者:Zhang, HW (reprint author), Dalian Univ Technol, Sch Math Sci, Dalian 116024, Liaoning, Peoples R China.

合写作者:Wu, Jun,Liu, Shenglan,Zhang, Hongwei

发表时间:2015-11-01

发表刊物:JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION

收录刊物:SCIE、EI、Scopus

卷号:33

页面范围:104-114

ISSN号:1047-3203

关键字:Image retrieval; HSV color space; Texton detection; Global Correlation Descriptor (GCD); Global Correlation Vector (GCV); Global Correlation Vector (DGCV); Feature fusion; Structure element correlation (SEC)

摘要:The image descriptors based on multi-features fusion have better performance than that based on simple feature in content-based image retrieval (CBIR). However, these methods still have some limitations: (1) the methods that define directly texture in color space put more emphasis on color than texture feature; (2) traditional descriptors based on histogram statistics disregard the spatial correlation between structure elements; (3) the descriptors based on structure element correlation (SEC) disregard the occurring probability of structure elements. To solve these problems, we propose a novel image descriptor, called Global Correlation Descriptor (GCD), to extract color and texture feature respectively so that these features have the same effect in CBIR. In addition, we propose Global Correlation Vector (GCV) and Directional Global Correlation Vector (DGCV) which can integrate the advantages of histogram statistics and SEC to characterize color and texture features respectively. Experimental results demonstrate that GCD is more robust and discriminative than other image descriptors in CBIR. (C) 2015 Elsevier Inc. All rights reserved.