Method of Detecting Sea State from Image Taken by Autonomous Surface Vehicle

Abstract:

Autonomous surface vehicle provides a safe approach to monitor environment on water surface in dangerous condition. This paper presents a method of sea state detection from images taken by a camera fixed on an autonomous surface vehicle. Based on texture feature of images from water surface scene, gray level co-occurrence matrix is computed, and its features including energy, contrast, correlation and entropy are extracted. Experiments show that the contrast can differentiate the sea state levels better than the others. To improve discrimination at low sea state levels, a transform is proposed. Performance of the method at different light shining conditions is discussed, and the results validate the method.

• Periodical: Applied Mechanics and Materials (Volumes 316-317)
• Pages: 475-478
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.316-317.475
• Online since: April 2013
• Authors: Jian Hua Wang, Gang Li, Ya Zhou Xiong, Kang Ke Liu
• Keywords: Autonomous Surface Vehicles, Environment Monitoring, Image, Sea State, Texture

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