ROV-based Underwater Vision System for Intelligent Fish Ethology Research

Fish ethology is a prospective discipline for ocean surveys. In this paper, one ROV-based system is established to perform underwater visual tasks with customized optical sensors installed. One image quality enhancement method is first presented in the context of creating underwater imaging models combined with homomorphic filtering and wavelet decomposition. The underwater vision system can further detect and track swimming fish from the resulting images with the strategies developed using curve evolution and particular filtering, in order to obtain a deeper understanding of fish behaviours. The simulation results have shown the excellent performance of the developed scheme, in regard to both robustness and effectiveness.

[1]  Ronald Fedkiw,et al.  Level set methods and dynamic implicit surfaces , 2002, Applied mathematical sciences.

[2]  Tamaki Ura,et al.  Vision-based underwater cable detection and following using AUVs , 2002, OCEANS '02 MTS/IEEE.

[3]  N. Tinbergen.  On aims and methods of Ethology , 2010 .

[4]  K. D. Moore,et al.  Underwater Optical Imaging: Status and Prospects , 2001 .

[5]  David I. Mostofsky,et al.  The behavior of fish and other aquatic animals , 1978 .

[6]  Luc Van Gool,et al.  An adaptive color-based particle filter , 2003, Image Vis. Comput..

[7]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[8]  Katja Nummiaro.  A Color-based Particle Filter , 2002 .

[9]  Peter I. Corke,et al.  Experiments with Underwater Robot Localization and Tracking , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[10]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[11]  A. Sekar,et al.  A Survey on Image Segmentation Techniques , 2015 .

[12]  H. Evans.  The Study of Instinct , 1952 .

[13]  J. Q. Smith.  Decision Analysis: A Bayesian Approach , 1988 .

[14]  Branko Ristic,et al.  A particle filter for joint detection and tracking of color objects , 2007, Image Vis. Comput..

[15]  James D. Watkins,et al.  AN OCEAN BLUEPRINT FOR THE 21ST CENTURY: THE WORK OF THE U.S. COMMISSION ON OCEAN POLICY , 2004 .

[16]  Tadahiro Hyakudome,et al.  Design of Autonomous Underwater Vehicle , 2011 .

[17]  Alex M. Andrew,et al.  Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (2nd edition) , 2000 .

[18]  Raimondo Schettini,et al.  Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods , 2010, EURASIP J. Adv. Signal Process..

[19]  Chao Li,et al.  Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing , 2011, Sensors.

[20]  J. Zaneveld,et al.  Robust underwater visibility parameter. , 2003, Optics express.

[21]  Anthony J. Yezzi,et al.  Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification , 2001, IEEE Trans. Image Process..

[22]  Andrew Hogue,et al.  A visually guided swimming robot , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Olivier D. Faugeras,et al.  CURVES: Curve evolution for vessel segmentation , 2001, Medical Image Anal..

[24]  William Rowan,et al.  The Study of Instinct , 1953 .

[25]  Martin W. Johnson,et al.  The Oceans, Their Physics, Chemistry and General Biology , 1945 .

[26]  N. Tinbergen.  On aims and methods of Ethology , 2010 .

[27]  Professor Miles H. A. Keenleyside.  Diversity and Adaptation in Fish Behaviour , 1979, Zoophysiology.

[28]  Xiao Feng,et al.  AUV SLAM and Experiments Using a Mechanical Scanning Forward-Looking Sonar , 2012, Sensors.

[29]  J. Sethian,et al.  FRONTS PROPAGATING WITH CURVATURE DEPENDENT SPEED: ALGORITHMS BASED ON HAMILTON-JACOB1 FORMULATIONS , 2003 .

[30]  Roland Glowinski,et al.  A three-stage operator-splitting/finite element method for the numerical simulation of liquid crystal flow , 2009 .

[31]  Malcolm B. Jones,et al.  Identification of patch structure within marine benthic landscapes using a remotely operated vehicle , 2003 .

[32]  V. Trenkel,et al.  Variability in natural behaviour, and observed reactions to an ROV, by mid-slope fish species , 2006 .

[33]  Martin W. Johnson,et al.  The oceans : their physics, chemistry, and general biology , 1943 .

[34]  Xiaodong Zhang,et al.  Scattering by pure seawater: effect of salinity. , 2009, Optics express.

[35]  J. Berger.  Statistical Decision Theory and Bayesian Analysis , 1988 .

[36]  Pierre Fréon,et al.  Review of fish associative behaviour: Toward a generalisation of the meeting point hypothesis , 2000, Reviews in Fish Biology and Fisheries.

[37]  Z Otremba,et al.  Modelling of the optical contrast of an oil film on a sea surface. , 2001, Optics express.

[38]  Dorin Comaniciu,et al.  Kernel-Based Object Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  Jules S. Jaffe,et al.  Computer modeling and the design of optimal underwater imaging systems , 1990 .

[40]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[41]  Michael B. Lowry,et al.  A comparison of methods for estimating fish assemblages associated with estuarine artificial reefs , 2011 .