Development of an image processing module for autonomous underwater vehicles through integration of visual recognition with stereoscopic image reconstruction

Yu-Hsien Lin, Shao Yu Chen, Chia Hung Tsou

Research output: Contribution to journalArticle

Abstract

This study investigated the development of visual recognition and stereoscopic imaging technology, applying them to the construction of an image processing system for autonomous underwater vehicles (AUVs). For the proposed visual recognition technology, a Hough transform was combined with an optical flow algorithm to detect the linear features and movement speeds of dynamic images; the proposed stereoscopic imaging technique employed a Harris corner detector to estimate the distance of the target. A physical AUV was constructed with a wide-angle lens camera and a binocular vision device mounted on the bow to provide image input. Subsequently, a simulation environment was established in Simscape Multibody and used to control the post-driver system of the stern, which contained horizontal and vertical rudder planes as well as the propeller. In static testing at National Cheng Kung University, physical targets were placed in a stability water tank; the study compared the analysis results obtained from various brightness and turbidity conditions in out-of-water and underwater environments. Finally, the dynamic testing results were combined with a fuzzy controller to output the real-time responses of the vehicle regarding the angles, rates of the rudder planes, and the propeller revolution speeds at various distances.

Original languageEnglish
Article number107
JournalJournal of Marine Science and Engineering
Volume7
Issue number4
DOIs
Publication statusPublished - 2019 Apr 1

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Autonomous underwater vehicles
autonomous underwater vehicle
Propellers
Image reconstruction
image processing
Image processing
Binocular vision
underwater environment
Camera lenses
Imaging techniques
Water tanks
Hough transforms
Optical flows
Testing
Turbidity
turbidity
Luminance
transform
Detectors
water

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Water Science and Technology
  • Ocean Engineering

Cite this

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abstract = "This study investigated the development of visual recognition and stereoscopic imaging technology, applying them to the construction of an image processing system for autonomous underwater vehicles (AUVs). For the proposed visual recognition technology, a Hough transform was combined with an optical flow algorithm to detect the linear features and movement speeds of dynamic images; the proposed stereoscopic imaging technique employed a Harris corner detector to estimate the distance of the target. A physical AUV was constructed with a wide-angle lens camera and a binocular vision device mounted on the bow to provide image input. Subsequently, a simulation environment was established in Simscape Multibody and used to control the post-driver system of the stern, which contained horizontal and vertical rudder planes as well as the propeller. In static testing at National Cheng Kung University, physical targets were placed in a stability water tank; the study compared the analysis results obtained from various brightness and turbidity conditions in out-of-water and underwater environments. Finally, the dynamic testing results were combined with a fuzzy controller to output the real-time responses of the vehicle regarding the angles, rates of the rudder planes, and the propeller revolution speeds at various distances.",
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