Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)

Image recognition algorithm based on Parameter Optimization of gravitational search

Authors
LEI Hu
Corresponding Author
LEI Hu
Available Online September 2016.
DOI
https://doi.org/10.2991/icence-16.2016.113How to use a DOI?
Keywords
Gravitational search algorithm; Parameter optimization; Image recognition
Abstract

Image characteristic value extracted by gravitational search algorithm improves the image retrieval accuracy. The distance between the image characteristic values is as the input value, accuracy of image recognition is calculated by pulse coupled network variates optimized of Gravitational search algorithm. The retrieval accuracy of pulse coupled network optimized by gravitational search algorithm improves by 7% at least than method of relevance feedback, color edge combined discrete wavelet transform.

Copyright
© 2016, 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 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-229-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icence-16.2016.113How to use a DOI?
Copyright
© 2016, 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  - LEI Hu
PY  - 2016/09
DA  - 2016/09
TI  - Image recognition algorithm based on Parameter Optimization of gravitational search
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 594
EP  - 598
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.113
DO  - https://doi.org/10.2991/icence-16.2016.113
ID  - Hu2016/09
ER  -