A Complete Process For Shipborne Sea-Ice Field Analysis Using Machine Vision

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

A sensor instrumentation and an automated process are proposed for sea-ice field analysis using ship mounted machine vision cameras with the help of inertial and satellite positioning sensors. The proposed process enables automated acquisition of sea-ice concentration, floes size and distribution. The process contains pre-processing steps such as sensor calibration, distortion removal, orthorectification of image data, and data extraction steps such as sea-ice floe clustering, detection, and analysis. In addition, we improve the state of the art of floe clustering and detection, by using an enhanced version of the k-means algorithm and the blue colour channel for increased contrast in ice detection. Comparing to manual visual observations, the proposed method gives significantly more detailed and frequent data about the size and distribution of individual floes. Through our initial experiments in pack ice conditions,the proposed system has proved to be able to segment most of the individual floes and estimate their size and area.
Original languageEnglish
Title of host publicationProceedings of the 21st IFAC World Congress, IFAC 2020
PublisherElsevier
Number of pages7
Edition21
Publication statusAccepted/In press - 17 Jul 2020
MoE publication typeA4 Article in a conference publication
EventIFAC World Congress - Virtual, Online
Duration: 11 Jul 202017 Jul 2020
Conference number: 21

Publication series

NameIFAC-PapersOnLine
PublisherElsevier
ISSN (Electronic)2405-8963

Conference

ConferenceIFAC World Congress
CityVirtual, Online
Period11/07/202017/07/2020
OtherVirtual

Keywords

  • machine vision
  • Sea-ice
  • k-means
  • dynamic thresholding
  • IMU
  • sensor integration
  • Decision Support System (DSS)

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