Content-based image retrieval using hybrid micro-structure descriptor

Ying Li; Pei Zhang

doi:10.1007/978-3-319-23989-7_42

Content-based image retrieval using hybrid micro-structure descriptor

Ying Li, Pei Zhang

School of Computer Science

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Along with the speedy increase in the size of digital image collections, the content-based image retrieval (CBIR) has already become one of the hot topics in both image processing and computer vision. And it has been widely used in browsing, searching, and retrieving certain interested information from a huge amount of data. In this paper, we present a hybrid micro-structure descriptor (HMSD) to describe the image feature, which is used for image retrieval. This method makes a color quantization and edge orientation detection of the image in both HSV and RGB color space to extract four kinds of micro-structure and then hybrid these four via an effective way. The experimental results show that the information of images such as color, texture, shape, and color layout can be described more effectively by using this method and the accuracy of image retrieval is improved greatly than several well-known methods.

Original language	English
Title of host publication	Intelligence Science and Big Data Engineering
Subtitle of host publication	Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers
Editors	Xiaofei He, Zhi-Hua Zhou, Xinbo Gao, Zhi-Yong Liu, Yanning Zhang, Baochuan Fu, Fuyuan Hu, Zhancheng Zhang
Publisher	Springer Verlag
Pages	411-419
Number of pages	9
ISBN (Print)	9783319239873
DOIs	https://doi.org/10.1007/978-3-319-23989-7_42
State	Published - 2015
Event	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 - Suzhou, China Duration: 14 Jun 2015 → 16 Jun 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9242
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015
Country/Territory	China
City	Suzhou
Period	14/06/15 → 16/06/15

Keywords

CBIR
Descriptor
Image retrieval
Micro-structure

Access to Document

10.1007/978-3-319-23989-7_42

Cite this

Li, Y., & Zhang, P. (2015). Content-based image retrieval using hybrid micro-structure descriptor. In X. He, Z.-H. Zhou, X. Gao, Z.-Y. Liu, Y. Zhang, B. Fu, F. Hu, & Z. Zhang (Eds.), Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers (pp. 411-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9242). Springer Verlag. https://doi.org/10.1007/978-3-319-23989-7_42

Li, Ying ; Zhang, Pei. / Content-based image retrieval using hybrid micro-structure descriptor. Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. editor / Xiaofei He ; Zhi-Hua Zhou ; Xinbo Gao ; Zhi-Yong Liu ; Yanning Zhang ; Baochuan Fu ; Fuyuan Hu ; Zhancheng Zhang. Springer Verlag, 2015. pp. 411-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Content-based image retrieval using hybrid micro-structure descriptor",

abstract = "Along with the speedy increase in the size of digital image collections, the content-based image retrieval (CBIR) has already become one of the hot topics in both image processing and computer vision. And it has been widely used in browsing, searching, and retrieving certain interested information from a huge amount of data. In this paper, we present a hybrid micro-structure descriptor (HMSD) to describe the image feature, which is used for image retrieval. This method makes a color quantization and edge orientation detection of the image in both HSV and RGB color space to extract four kinds of micro-structure and then hybrid these four via an effective way. The experimental results show that the information of images such as color, texture, shape, and color layout can be described more effectively by using this method and the accuracy of image retrieval is improved greatly than several well-known methods.",

keywords = "CBIR, Descriptor, Image retrieval, Micro-structure",

author = "Ying Li and Pei Zhang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 ; Conference date: 14-06-2015 Through 16-06-2015",

year = "2015",

doi = "10.1007/978-3-319-23989-7_42",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Li, Y & Zhang, P 2015, Content-based image retrieval using hybrid micro-structure descriptor. in X He, Z-H Zhou, X Gao, Z-Y Liu, Y Zhang, B Fu, F Hu & Z Zhang (eds), Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9242, Springer Verlag, pp. 411-419, 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, Suzhou, China, 14/06/15. https://doi.org/10.1007/978-3-319-23989-7_42

Content-based image retrieval using hybrid micro-structure descriptor. / Li, Ying; Zhang, Pei.
Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. ed. / Xiaofei He; Zhi-Hua Zhou; Xinbo Gao; Zhi-Yong Liu; Yanning Zhang; Baochuan Fu; Fuyuan Hu; Zhancheng Zhang. Springer Verlag, 2015. p. 411-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9242).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Content-based image retrieval using hybrid micro-structure descriptor

AU - Li, Ying

AU - Zhang, Pei

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Along with the speedy increase in the size of digital image collections, the content-based image retrieval (CBIR) has already become one of the hot topics in both image processing and computer vision. And it has been widely used in browsing, searching, and retrieving certain interested information from a huge amount of data. In this paper, we present a hybrid micro-structure descriptor (HMSD) to describe the image feature, which is used for image retrieval. This method makes a color quantization and edge orientation detection of the image in both HSV and RGB color space to extract four kinds of micro-structure and then hybrid these four via an effective way. The experimental results show that the information of images such as color, texture, shape, and color layout can be described more effectively by using this method and the accuracy of image retrieval is improved greatly than several well-known methods.

AB - Along with the speedy increase in the size of digital image collections, the content-based image retrieval (CBIR) has already become one of the hot topics in both image processing and computer vision. And it has been widely used in browsing, searching, and retrieving certain interested information from a huge amount of data. In this paper, we present a hybrid micro-structure descriptor (HMSD) to describe the image feature, which is used for image retrieval. This method makes a color quantization and edge orientation detection of the image in both HSV and RGB color space to extract four kinds of micro-structure and then hybrid these four via an effective way. The experimental results show that the information of images such as color, texture, shape, and color layout can be described more effectively by using this method and the accuracy of image retrieval is improved greatly than several well-known methods.

KW - CBIR

KW - Descriptor

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DO - 10.1007/978-3-319-23989-7_42

M3 - 会议稿件

AN - SCOPUS:84951751075

SN - 9783319239873

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 411

EP - 419

BT - Intelligence Science and Big Data Engineering

A2 - He, Xiaofei

A2 - Zhou, Zhi-Hua

A2 - Gao, Xinbo

A2 - Liu, Zhi-Yong

A2 - Zhang, Yanning

A2 - Fu, Baochuan

A2 - Hu, Fuyuan

A2 - Zhang, Zhancheng

PB - Springer Verlag

T2 - 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015

Y2 - 14 June 2015 through 16 June 2015

ER -

Li Y, Zhang P. Content-based image retrieval using hybrid micro-structure descriptor. In He X, Zhou ZH, Gao X, Liu ZY, Zhang Y, Fu B, Hu F, Zhang Z, editors, Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. Springer Verlag. 2015. p. 411-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23989-7_42

Content-based image retrieval using hybrid micro-structure descriptor

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Keywords

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