Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

Image Stitching Method Based on Genetic Algorithm

Authors
Yang Xu, Changbo Sun
Corresponding Author
Yang Xu
Available Online April 2017.
DOI
10.2991/icmmct-17.2017.87How to use a DOI?
Keywords
image stitching, genetic algorithm, image fusion, RAnSAC, Laplacian pyramid
Abstract

In allusion to the inaccuracy of homography matrix using RAnSAC from image stitching based on image features,a new image stitching algorithm based on genetic algorithm was proposed.First,locate and describe the feature points of images using feature extraction algorithm,and and the coarse matching was performed based on the ratio between nearest distance and next nearest distance. Then get optimal transform model using genetic algorithm. At last, use the Laplacian transform pyramid reconstruction algorithm to reconstruct and obtain the final fused image. The experiment show that compared with common methods, the method proposed in this paper performs better in terms of accuracy of homography matrix. Subjectively, it improves the quality and effect of fusion image.

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 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/icmmct-17.2017.87
ISSN
2352-5401
DOI
10.2991/icmmct-17.2017.87How 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

TY  - CONF
AU  - Yang Xu
AU  - Changbo Sun
PY  - 2017/04
DA  - 2017/04
TI  - Image Stitching Method Based on Genetic Algorithm
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 406
EP  - 412
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.87
DO  - 10.2991/icmmct-17.2017.87
ID  - Xu2017/04
ER  -