Graph based image matching
Given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern discovery. These problems have different levels of purpose and difficulties, as a result, often associate with different solut...
Saved in:
Main Authors: | , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2004
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/6554 https://ink.library.smu.edu.sg/context/sis_research/article/7557/viewcontent/icpr04_d.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-7557 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-75572022-01-10T03:37:08Z Graph based image matching JIANG, Hui NGO, Chong-wah Given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern discovery. These problems have different levels of purpose and difficulties, as a result, often associate with different solutions. In this paper, we propose a novel approach to solve these problems under a unified framework based on graph matching. We first split the images into small blocks and represent each block as a node in a bipartite graph. A maximum weighted bipartite graph matching algorithm is then employed in an iterative way to find the best transformation set. Experimental results show that our approach can handle rotation, scaling and translation, as well as distortion and occlusion. Another virtue of our approach is its efficiency 2004-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6554 info:doi/10.1109/ICPR.2004.1334615 https://ink.library.smu.edu.sg/context/sis_research/article/7557/viewcontent/icpr04_d.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Graphics and Human Computer Interfaces |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Computer Sciences Graphics and Human Computer Interfaces |
spellingShingle |
Computer Sciences Graphics and Human Computer Interfaces JIANG, Hui NGO, Chong-wah Graph based image matching |
description |
Given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern discovery. These problems have different levels of purpose and difficulties, as a result, often associate with different solutions. In this paper, we propose a novel approach to solve these problems under a unified framework based on graph matching. We first split the images into small blocks and represent each block as a node in a bipartite graph. A maximum weighted bipartite graph matching algorithm is then employed in an iterative way to find the best transformation set. Experimental results show that our approach can handle rotation, scaling and translation, as well as distortion and occlusion. Another virtue of our approach is its efficiency |
format |
text |
author |
JIANG, Hui NGO, Chong-wah |
author_facet |
JIANG, Hui NGO, Chong-wah |
author_sort |
JIANG, Hui |
title |
Graph based image matching |
title_short |
Graph based image matching |
title_full |
Graph based image matching |
title_fullStr |
Graph based image matching |
title_full_unstemmed |
Graph based image matching |
title_sort |
graph based image matching |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2004 |
url |
https://ink.library.smu.edu.sg/sis_research/6554 https://ink.library.smu.edu.sg/context/sis_research/article/7557/viewcontent/icpr04_d.pdf |
_version_ |
1770575987138887680 |