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Fast Underwater Image Mosaicing through Submapping

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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.

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Authors and Affiliations

  1. School of Integrated Technology, Yonsei Institute of Convergence Technology, Yonsei University, Incheon, Republic of Korea

    Armagan Elibol

  2. Department of Mathematical Engineering, Yildiz Technical University, Istanbul, Turkey

    Armagan Elibol

  3. Mobile Robotics and Intelligence Laboratory, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

    Jinwhan Kim

  4. Computer Vision and Robotics Institute, University of Girona, Girona, Spain

    Nuno Gracias & Rafael Garcia

Authors
  1. Armagan Elibol
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  2. Jinwhan Kim
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  3. Nuno Gracias
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  4. Rafael Garcia
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Correspondence to Armagan Elibol.

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Elibol, A., Kim, J., Gracias, N. et al. Fast Underwater Image Mosaicing through Submapping. J Intell Robot Syst 85, 167–187 (2017). https://doi.org/10.1007/s10846-016-0380-x

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