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/).

Download article (PDF)

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  -