Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)

The Research of Techniques in Content-based Image Retrieval

Authors
Jing Chang, Dong Liu
Corresponding Author
Jing Chang
Available Online July 2019.
DOI
10.2991/iccia-19.2019.76How to use a DOI?
Keywords
image retrieval; feature extraction; Similarity matrix.
Abstract

Image feature extraction is the realization of content-based image retrieval based on the first step, but also is the most critical step. Image feature extraction is suitable or not directly affect the performance of image retrieval system, this paper describes the features of the image, and construct a feature-based similarity metric matrix. By using these matrix combinations, a kernel based image similarity measurement matrix is constructed, which lays the foundation for the clustering processing of similarity matrix.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
Series
Advances in Computer Science Research
Publication Date
July 2019
ISBN
10.2991/iccia-19.2019.76
ISSN
2352-538X
DOI
10.2991/iccia-19.2019.76How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jing Chang
AU  - Dong Liu
PY  - 2019/07
DA  - 2019/07
TI  - The Research of Techniques in Content-based Image Retrieval
BT  - Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
PB  - Atlantis Press
SP  - 490
EP  - 494
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-19.2019.76
DO  - 10.2991/iccia-19.2019.76
ID  - Chang2019/07
ER  -