Content-based image retrieval using color and texture fused features

被引：171
|
作者：
Yue, Jun [1 ,2 ]
Li, Zhenbo [1 ]
Liu, Lu [1 ]
Fu, Zetian [1 ]
机构：
[1] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
[2] LUDONG Univ, Sch Informat Sci & Engn, Yantai 264025, Peoples R China
来源：
MATHEMATICAL AND COMPUTER MODELLING | 2011年 / 54卷 / 3-4期
关键词：
Content based image retrieval; HSV; Color; Texture;
D O I：
10.1016/j.mcm.2010.11.044
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents a method to extract color and texture features of an image quickly for content-based image retrieval (CBIR). First, HSV color space is quantified rationally. Color histogram and texture features based on a co-occurrence matrix are extracted to form feature vectors. Then the characteristics of the global color histogram, local color histogram and texture features are compared and analyzed for CBIR. Based on these works, a CBIR system is designed using color and texture fused features by constructing weights of feature vectors. The relevant retrieval experiments show that the fused features retrieval brings better visual feeling than the single feature retrieval, which means better retrieval results. (c) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1121 / 1127
页数：7
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