Journal of Intelligent & Robotic Systems

, Volume 85, Issue 1, pp 167–187

Fast Underwater Image Mosaicing through Submapping

  • Armagan Elibol
  • Jinwhan Kim
  • Nuno Gracias
  • Rafael Garcia
Article

DOI: 10.1007/s10846-016-0380-x

Cite this article as:
Elibol, A., Kim, J., Gracias, N. et al. J Intell Robot Syst (2017) 85: 167. doi:10.1007/s10846-016-0380-x
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Abstract

One of the most important features of mobile robots is their capability to gather data from areas beyond human reach. This capability has increased the demand for the use of robots undertaking exploration tasks, which has naturally led to the need for efficient methods to process the obtained data. Image mosaicing is a useful tool for obtaining a high-resolution visual representation of a large area that has been explored using optical sensors. In this paper, we present an efficient image mosaicing approach that utilizes submapping methods to obtain a map of a surveyed area with reduced computational effort. The approach uses a modified agglomerative hierarchical clustering method to form submaps according to similarity information obtained through feature descriptor matching, and takes advantage of this submapping to reduce the computation and time costs. Comparative results on real challenging underwater datasets are presented.

Keywords

Image mosaicing Visual mapping Underwater robotics 

Funding information

Funder NameGrant NumberFunding Note
MSIP (Ministry of Science, ICT and Future Planning), Rep. of Korea
  • “IT Consilience Creative Program” (NIPA-2014-H0201-14-1002)
Ministry of Oceans and Fisheries, Rep. of Korea
  • “development of an autonomous ship-hull inspection system”
Spanish Ministry of Economy and Competitiveness (MINECO)
  • CTM2013-46718-R (OMNIUS)
EU project
  • FP7-INF-2012-312762 (Eurofleets2)
US DoD/DoE/EPA/ESTCP
  • project SI2010
Generalitat de Catalunya ACCIO/TecnioSpring program
  • (TECSPR14-1-0050)

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Armagan Elibol
    • 1
    • 2
  • Jinwhan Kim
    • 3
  • Nuno Gracias
    • 4
  • Rafael Garcia
    • 4
  1. 1.School of Integrated TechnologyYonsei Institute of Convergence Technology, Yonsei UniversityIncheonRepublic of Korea
  2. 2.Department of Mathematical EngineeringYildiz Technical UniversityIstanbulTurkey
  3. 3.Mobile Robotics and Intelligence Laboratory, Department of Mechanical EngineeringKorea Advanced Institute of Science and Technology (KAIST)DaejeonRepublic of Korea
  4. 4.Computer Vision and Robotics InstituteUniversity of GironaGironaSpain

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