Image Matching Based on Election Campaign Algorithm
- DOI
- 10.2991/meici-16.2016.259How to use a DOI?
- Keywords
- Image matching; Grey scale feature; Rotation invariant feature; Election campaign algorithm
- Abstract
Image matching is widely used in image analysis and computer vision. Traditional Image matching method is to move the template in the reference image pixel by pixel, calculate their gray similarity. It has high computational complexity. If there is a rotation between the template and the reference map, the traditional matching method is difficult to achieve in real time. A method is proposed for matching rotated images based on gray scale feature in this paper, we use Election Campaign Algorithm detect the gray scale feature of points, then rotation invariant feature model, finally using rotation invariant feature model matching point set, image acquisition the translation and rotation parameters. The result of this method is accurate, and the computation complexity is small compared with the traditional correlation matching method, and it is easy to implement in real time.
- 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 - Qinghua Xie AU - Xiangwei Zhang AU - Wenge Lv AU - Siyuan Cheng PY - 2016/09 DA - 2016/09 TI - Image Matching Based on Election Campaign Algorithm BT - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016) PB - Atlantis Press SP - 1244 EP - 1248 SN - 1951-6851 UR - https://doi.org/10.2991/meici-16.2016.259 DO - 10.2991/meici-16.2016.259 ID - Xie2016/09 ER -