Detecting floods using an object based change detection approach
In change detection analysis, it is important to reduce the influence of image misalignment in order to produce image changes that are relevant to the user. The accuracy of change detection solely depends on the image registration accuracy yet image misalignment is still a major challenge in chan...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Book Section |
Published: |
IEEE
2012
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/34710/ http://dx.doi.org/10.1109/ICCCE.2012.6271149 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.34710 |
---|---|
record_format |
eprints |
spelling |
my.utm.347102017-02-02T05:26:02Z http://eprints.utm.my/id/eprint/34710/ Detecting floods using an object based change detection approach Faiza, B. Yuhaniz, Siti Sophiayati Mohd. Hashim, Siti Zaiton Kalema , A. K. QA75 Electronic computers. Computer science In change detection analysis, it is important to reduce the influence of image misalignment in order to produce image changes that are relevant to the user. The accuracy of change detection solely depends on the image registration accuracy yet image misalignment is still a major challenge in change detection analysis. In change detection analysis, if change detection is performed on misaligned images, problems such as false changes and missed changes may occur which strongly affect the actual change detection accuracy. Object based change detection has been reported as one the best way to reduce the influence of effects of image misalignment. This is because of its capability to deal with misregistration errors that result into false change and missed changes. In this paper, a tiled object based change detection technique is proposed to reduce the influence of image misalignment on the tile pixel based change detection. Threshold level based fuzzy c-mean clustering is adopted during segmentation and classification, as well as image differencing is used to obtain a change image. Experiments show that the proposed method significantly reduces the false changes (commission error (from 16.67% to 0.7059%, 40.63% to 1.3881%, 31.58% to 2.1034%) in tile pixel based change detection meaning the method is robust to noise. The experimental results show that the method is capable of producing a high accuracy rate. IEEE 2012 Book Section PeerReviewed Faiza, B. and Yuhaniz, Siti Sophiayati and Mohd. Hashim, Siti Zaiton and Kalema , A. K. (2012) Detecting floods using an object based change detection approach. In: 2012 International Conference on Computer and Communication Engineering, ICCCE 2012. IEEE, New York, USA, pp. 44-50. ISBN 978-146730478-8 http://dx.doi.org/10.1109/ICCCE.2012.6271149 DOI:10.1109/ICCCE.2012.6271149 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
QA75 Electronic computers. Computer science |
spellingShingle |
QA75 Electronic computers. Computer science Faiza, B. Yuhaniz, Siti Sophiayati Mohd. Hashim, Siti Zaiton Kalema , A. K. Detecting floods using an object based change detection approach |
description |
In change detection analysis, it is important to reduce the influence of image misalignment in order to produce image changes that are relevant to the user. The accuracy of change detection solely depends on the image registration accuracy yet image misalignment is still a major challenge in change detection analysis. In change detection analysis, if change detection is performed on misaligned images, problems such as false changes and missed changes may occur which strongly affect the actual change detection accuracy. Object based change detection has been reported as one the best way to reduce the influence of effects of image misalignment. This is because of its capability to deal with misregistration errors that result into false change and missed changes. In this paper, a tiled object based change detection technique is proposed to reduce the influence of image misalignment on the tile pixel based change detection. Threshold level based fuzzy c-mean clustering is adopted during segmentation and classification, as well as image differencing is used to obtain a change image. Experiments show that the proposed method significantly reduces the false changes (commission error (from 16.67% to 0.7059%, 40.63% to 1.3881%, 31.58% to 2.1034%) in tile pixel based change detection meaning the method is robust to noise. The experimental results show that the method is capable of producing a high accuracy rate. |
format |
Book Section |
author |
Faiza, B. Yuhaniz, Siti Sophiayati Mohd. Hashim, Siti Zaiton Kalema , A. K. |
author_facet |
Faiza, B. Yuhaniz, Siti Sophiayati Mohd. Hashim, Siti Zaiton Kalema , A. K. |
author_sort |
Faiza, B. |
title |
Detecting floods using an object based change detection approach |
title_short |
Detecting floods using an object based change detection approach |
title_full |
Detecting floods using an object based change detection approach |
title_fullStr |
Detecting floods using an object based change detection approach |
title_full_unstemmed |
Detecting floods using an object based change detection approach |
title_sort |
detecting floods using an object based change detection approach |
publisher |
IEEE |
publishDate |
2012 |
url |
http://eprints.utm.my/id/eprint/34710/ http://dx.doi.org/10.1109/ICCCE.2012.6271149 |
_version_ |
1643649652262699008 |
score |
13.160551 |