Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

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The Research of SURF Image Matching Method Based on Region and Feature Information

Authors
Rongbao Chen, Qianlong Wang, Honghui Jiang, Yang Liu, Dawei Tang
Corresponding Author
Rongbao Chen
Available Online November 2017.
DOI
10.2991/amms-17.2017.13How to use a DOI?
Keywords
SURF feature matching; dense matching; constraints; feature points; region matching
Abstract

According to the SURF feature matching dense matching interpolation algorithm to realize the problems in the complex dynamic background image. The dynamic camera captured the same environment as the object. SURF image is proposed based on the combination of region and the feature information matching method. Firstly, image gray-scale normalization. There may be a reduction the brightness of light due to the translational response point of view. And then add several constraints in the process of extracting SURF feature points. Not only can speed up the matching process, but also can reduce the false match rate. Finally, in order to detect the feature points as the seed point for regional growth, the seed region division of the region by using graph matching. The test show that the algorithm can obtain dense disparity images of good. After the camera shooting of different sizes of image feature matching. Experiments show that, Compared with the SIFT algorithm and the SURF algorithm, the algorithm reduces the number of feature points and matching points, and improves the matching accuracy and the matching accuracy.

Copyright
© 2017, 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 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
10.2991/amms-17.2017.13
ISSN
1951-6851
DOI
10.2991/amms-17.2017.13How to use a DOI?
Copyright
© 2017, 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

risenwbib
TY  - CONF
AU  - Rongbao Chen
AU  - Qianlong Wang
AU  - Honghui Jiang
AU  - Yang Liu
AU  - Dawei Tang
PY  - 2017/11
DA  - 2017/11
TI  - The Research of SURF Image Matching Method Based on Region and Feature Information
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 58
EP  - 65
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.13
DO  - 10.2991/amms-17.2017.13
ID  - Chen2017/11
ER  -