Synthetic imagery for the automated detection of rip currents

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

*Corresponding author for this work

Research output: Contribution to journalConference paperpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)912-916
Number of pages5
JournalJournal of Coastal Research
Volume1
Issue number75
DOIs
Publication statusPublished - 1 Mar 2016
Event14th International Coastal Symposium - Sydney, Australia
Duration: 6 Mar 201611 Mar 2016

Keywords

  • Coastal imaging
  • Image filtering
  • Remote sensing
  • Rip channel
  • Synthetic imagery

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