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Synthetic imagery for the automated detection of rip currents

Synthetic imagery for the automated detection of rip currents
Synthetic imagery for the automated detection of rip currents
Rip currents are a major hazard on beaches worldwide. Although it is in-situ measurements of rips can be made in the field, it is generally safer and more cost effective to employ remote sensing methods, such as coastal video imaging systems. However, there is no universal, fully-automated method capable of detecting rips in imagery. In this paper we discuss the benefits of image manipulation, such as filtering, prior to rip detection attempts. Furthermore, we present a new approach to detect rip channels that utilizes synthetic imagery. The creation of a synthetic image involves zonation of the ‘parent’ image into key areas, such as sand bars, channels, shoreline and offshore. Then, pixels in each zone are replaced with the respective dominant color trends observed in the parent image. Using synthetic imagery increased the accuracy of rip detection from 81% to 92%. Synthetics reduce ‘noise’ inherent in surfzone imagery and is another step towards an automated approach for rip current detection.
0749-0208
912-916
Pitman, Sebastian
7657cca5-521d-4731-801a-efb3d9a9efc2
Gallop, Shari L.
c14133fc-9141-47d9-ae9c-84c2513ea8ad
Haigh, Ivan D.
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Mahmoodi, Susan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Masselink, Gerd
c56ad11b-b88a-48cd-86aa-0c6cec5759f3
Ranasinghe, Roshanka
595401f8-1450-454d-b9ec-1ea3de9eebb4
Pitman, Sebastian
7657cca5-521d-4731-801a-efb3d9a9efc2
Gallop, Shari L.
c14133fc-9141-47d9-ae9c-84c2513ea8ad
Haigh, Ivan D.
945ff20a-589c-47b7-b06f-61804367eb2d
Mahmoodi, Susan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Masselink, Gerd
c56ad11b-b88a-48cd-86aa-0c6cec5759f3
Ranasinghe, Roshanka
595401f8-1450-454d-b9ec-1ea3de9eebb4

Pitman, Sebastian, Gallop, Shari L., Haigh, Ivan D., Mahmoodi, Susan, Masselink, Gerd and Ranasinghe, Roshanka (2016) Synthetic imagery for the automated detection of rip currents. Journal of Coastal Research, Special Issue (75), 912-916. (doi:10.2112/SI75-183.1).

Record type: Article

Abstract

Rip currents are a major hazard on beaches worldwide. Although it is in-situ measurements of rips can be made in the field, it is generally safer and more cost effective to employ remote sensing methods, such as coastal video imaging systems. However, there is no universal, fully-automated method capable of detecting rips in imagery. In this paper we discuss the benefits of image manipulation, such as filtering, prior to rip detection attempts. Furthermore, we present a new approach to detect rip channels that utilizes synthetic imagery. The creation of a synthetic image involves zonation of the ‘parent’ image into key areas, such as sand bars, channels, shoreline and offshore. Then, pixels in each zone are replaced with the respective dominant color trends observed in the parent image. Using synthetic imagery increased the accuracy of rip detection from 81% to 92%. Synthetics reduce ‘noise’ inherent in surfzone imagery and is another step towards an automated approach for rip current detection.

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More information

Accepted/In Press date: 15 January 2016
Published date: March 2016
Venue - Dates: 14th International Coastal Symposium, Australia, 2016-03-06 - 2016-03-11
Related URLs:
Organisations: Vision, Learning and Control, Geology & Geophysics, Physical Oceanography

Identifiers

Local EPrints ID: 382699
URI: http://eprints.soton.ac.uk/id/eprint/382699
ISSN: 0749-0208
PURE UUID: c97206c3-a278-405f-b10b-904c5f7444c2

Catalogue record

Date deposited: 09 Oct 2015 10:19
Last modified: 16 Dec 2019 20:13

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Contributors

Author: Sebastian Pitman
Author: Shari L. Gallop
Author: Ivan D. Haigh
Author: Susan Mahmoodi
Author: Gerd Masselink
Author: Roshanka Ranasinghe

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