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 change...

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Main Authors: Faiza, B., Yuhaniz, Siti Sophiayati, Mohd. Hashim, S. Z., Kalema, A. K.
Format: Conference or Workshop Item
Published: 2012
Online Access:http://eprints.utm.my/id/eprint/34050/
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spelling my.utm.340502017-09-07T04:09:19Z http://eprints.utm.my/id/eprint/34050/ Detecting floods using an object based change detection approach Faiza, B. Yuhaniz, Siti Sophiayati Mohd. Hashim, S. Z. Kalema, A. K. 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. 2012 Conference or Workshop Item PeerReviewed Faiza, B. and Yuhaniz, Siti Sophiayati and Mohd. Hashim, S. Z. and Kalema, A. K. (2012) Detecting floods using an object based change detection approach. In: 4th International Conference on Computer and Communication Engineering.
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/
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 Conference or Workshop Item
author Faiza, B.
Yuhaniz, Siti Sophiayati
Mohd. Hashim, S. Z.
Kalema, A. K.
spellingShingle Faiza, B.
Yuhaniz, Siti Sophiayati
Mohd. Hashim, S. Z.
Kalema, A. K.
Detecting floods using an object based change detection approach
author_facet Faiza, B.
Yuhaniz, Siti Sophiayati
Mohd. Hashim, S. Z.
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
publishDate 2012
url http://eprints.utm.my/id/eprint/34050/
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score 13.211869