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Synthetic imagery for the automated detection of rip currents

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Pitman, Sebastian
Gallop, Shari L.
Haigh, Ivan D.
Mahmoodi, Sasan
Masselink, Gerd
Ranasinghe, Roshanka

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Rip currents are a major hazard on beaches worldwide. Although 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 the partitioning of the 'parent' image into key areas, such as sand bars, channels, shoreline and offshore. Then, pixels in each partition 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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Journal of Coastal Research

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