Image retrieval based on multi-texton histogram

被引:219
作者
Liu, Guang-Hai [1 ]
Zhang, Lei [2 ]
Hou, Ying-Kun [4 ]
Li, Zuo-Yong [3 ]
Yang, Jing-Yu [3 ]
机构
[1] Guangxi Normal Univ, Coll Comp Sci & Informat Technol, Guilin 541004, Peoples R China
[2] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China
[3] Nanjing Univ Sci & Technol, Dept Comp Sci, Nanjing 210094, Peoples R China
[4] Taishan Univ, Sch Informat Sci & Technol, Tai An 271021, Shandong, Peoples R China
关键词
Image retrieval; Texton detection; Multi-texton histogram; COMBINING COLOR; RECOGNITION; FEATURES;
D O I
10.1016/j.patcog.2010.02.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a novel image feature representation method, called multi-texton histogram (MTH), for image retrieval. MTH integrates the advantages of co-occurrence matrix and histogram by representing the attribute of co-occurrence matrix using histogram. It can be considered as a generalized visual attribute descriptor but without any image segmentation or model training. The proposed MTH method is based on Julesz's textons theory, and it works directly on natural images as a shape descriptor. Meanwhile, it can be used as a color texture descriptor and leads to good performance. The proposed MTH method is extensively tested on the Corel dataset with 15 000 natural images. The results demonstrate that it is much more efficient than representative image feature descriptors, such as the edge orientation auto-correlogram and the texton co-occurrence matrix. It has good discrimination power of color, texture and shape features. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2380 / 2389
页数:10
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