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Image retrieval based on multi-texton histogram

delete2010-07-01
delete217
PRE
AI
刘
刘广海 (Guanghai Liu) *
张磊 cover
张磊 (Lei Zhang)
Y
Yingkun Hou
李佐勇 cover
李佐勇 (Zuoyong Li)
杨敬钰 cover
杨敬钰 (Jingyu Yang)
DOI:10.1016/j.patcog.2010.02.012delete
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Abstract

Abstract

En 中文
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.
Keywords:
Image retrieval
Texton detection
Multi-texton histogram
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.3W
Citations:
4.5W

Organization

H
hong kong polytechnic university
Scholars:
3.0W
Papers: 4.1W
Citations: 921
G
Guangxi Normal University
Scholars:
7.7K
Papers: 4.9K
Citations: 5.1K
T
Taishan University
Scholars:
669
Papers: 710
Citations: 1.1K
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