Research on Infrared and Visible Images Registration Algorithm Based on Graph

In this paper, we proposed a registration algorithm based on the combination of pyramid hierarchical idea and graph theory. It can solve the challenging problem of extracting consistent characteristics and matching the infrared and visible images. First, extracting the maximally stable extremal regi...

Full description

Bibliographic Details
Main Authors: Zhu Xiao-Lin, Hao Ying-Guang, Wang Hong-Yu
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:ITM Web of Conferences
Online Access:https://doi.org/10.1051/itmconf/20171102002
id doaj-be60d7e275d14dd68af742404de7ee8c
record_format Article
spelling doaj-be60d7e275d14dd68af742404de7ee8c2021-03-02T09:29:32ZengEDP SciencesITM Web of Conferences2271-20972017-01-01110200210.1051/itmconf/20171102002itmconf_ist2017_02002Research on Infrared and Visible Images Registration Algorithm Based on GraphZhu Xiao-Lin0Hao Ying-Guang1Wang Hong-Yu2Dalian University of Technology, School of Information and Communication EngineeringDalian University of Technology, School of Information and Communication EngineeringDalian University of Technology, School of Information and Communication EngineeringIn this paper, we proposed a registration algorithm based on the combination of pyramid hierarchical idea and graph theory. It can solve the challenging problem of extracting consistent characteristics and matching the infrared and visible images. First, extracting the maximally stable extremal regions (MSERs) in the determining maximum down-sampling images and each MSER is represented by a polygon. Then constructing the gragh features and the mapping relationship of MSERs between the infrared and visible images are determined by the graph matching method. Next we can construct the initial point set for matching according to the mapping relationship. Finally, using the random sample consensus (RANSAC) algorithm to obtain the optimal parameters and determine the error evaluation parameters. According to the idea of pyramid stratification, the above process is repeated in the high resolution images under the constraint condition of current matching error. The experiment results show that the algorithm can make full use of the visual similarity structures between images, and can achieve a smaller matching error under the premise of ensuring the robustness of the matching.https://doi.org/10.1051/itmconf/20171102002
collection DOAJ
language English
format Article
sources DOAJ
author Zhu Xiao-Lin
Hao Ying-Guang
Wang Hong-Yu
spellingShingle Zhu Xiao-Lin
Hao Ying-Guang
Wang Hong-Yu
Research on Infrared and Visible Images Registration Algorithm Based on Graph
ITM Web of Conferences
author_facet Zhu Xiao-Lin
Hao Ying-Guang
Wang Hong-Yu
author_sort Zhu Xiao-Lin
title Research on Infrared and Visible Images Registration Algorithm Based on Graph
title_short Research on Infrared and Visible Images Registration Algorithm Based on Graph
title_full Research on Infrared and Visible Images Registration Algorithm Based on Graph
title_fullStr Research on Infrared and Visible Images Registration Algorithm Based on Graph
title_full_unstemmed Research on Infrared and Visible Images Registration Algorithm Based on Graph
title_sort research on infrared and visible images registration algorithm based on graph
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2017-01-01
description In this paper, we proposed a registration algorithm based on the combination of pyramid hierarchical idea and graph theory. It can solve the challenging problem of extracting consistent characteristics and matching the infrared and visible images. First, extracting the maximally stable extremal regions (MSERs) in the determining maximum down-sampling images and each MSER is represented by a polygon. Then constructing the gragh features and the mapping relationship of MSERs between the infrared and visible images are determined by the graph matching method. Next we can construct the initial point set for matching according to the mapping relationship. Finally, using the random sample consensus (RANSAC) algorithm to obtain the optimal parameters and determine the error evaluation parameters. According to the idea of pyramid stratification, the above process is repeated in the high resolution images under the constraint condition of current matching error. The experiment results show that the algorithm can make full use of the visual similarity structures between images, and can achieve a smaller matching error under the premise of ensuring the robustness of the matching.
url https://doi.org/10.1051/itmconf/20171102002
work_keys_str_mv AT zhuxiaolin researchoninfraredandvisibleimagesregistrationalgorithmbasedongraph
AT haoyingguang researchoninfraredandvisibleimagesregistrationalgorithmbasedongraph
AT wanghongyu researchoninfraredandvisibleimagesregistrationalgorithmbasedongraph
_version_ 1724239324272132096