Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)

Central-Type Fusion-based Methods for Degraded Image Understanding

Authors
Cui Zhang, Xiu jun Zhang, Sheng ying Zhao, Li na Shang, Kai Xiong
Corresponding Author
Cui Zhang
Available Online August 2013.
DOI
https://doi.org/10.2991/icacsei.2013.35How to use a DOI?
Keywords
Degraded image, Dempster-Shafer evidence theory, Central-Type Fusion, Target recogniton
Abstract
Information fusion in target recognition is widely used, and application of information fusion in image field is developing continuously. When the degraded image is acquired, we often use the clearness algorithm to enhance image quality, Then the image of the target is identified, due to the lack of clarity of the image itself, the recognition accuracy is not high. Using a fusion rule of Dempster-Shafer evidence theory, the recognition algorithm of different posterior credibility is fusion, in order to get better recognition effect. This paper provides a fusion method for target recognition, the target exists in the degraded image. the fusion method is based on Central-Type algorithm of DS evidence theory. The results show that the method can improve the probability of correct recognition, reduce the error probability.
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Proceedings
2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90-78677-74-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/icacsei.2013.35How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Cui Zhang
AU  - Xiu jun Zhang
AU  - Sheng ying Zhao
AU  - Li na Shang
AU  - Kai Xiong
PY  - 2013/08
DA  - 2013/08
TI  - Central-Type Fusion-based Methods for Degraded Image Understanding
BT  - 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icacsei.2013.35
DO  - https://doi.org/10.2991/icacsei.2013.35
ID  - Zhang2013/08
ER  -