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Image Matching Using High Dynamic Range Images and Radial Feature Descriptors

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Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5358))

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Abstract

Obtaining a top match for a given query image from a set of images forms an important part of the scene identification process. The query image typically is not identical to the images in the data set, with possible variations of changes in scale, viewing angle and lighting conditions. Therefore, features which are used to describe each image should be invariant to these changes. Standard image capturing devices lose much of the color and lighting information due to encoding during image capture. This paper uses high dynamic range images to utilize all the details obtained at the time of capture for image matching. Once the high dynamic range images are obtained through the fusion of low dynamic range images, feature detection is performed on the query images as well as on the images in the database. A junction detector algorithm is used for detecting the features in the image. The features are described using the wedge descriptor which is modified to adapt to high dynamic range images. Once the features are described, a voting algorithm is used to identify a set of top matches for the query image.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Texas Tech University, Box 43104, Lubbock, TX 79409-3104, USA

    Krishnaprasad Jagadish & Eric Sinzinger

Authors
  1. Krishnaprasad Jagadish
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  2. Eric Sinzinger
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Jagadish, K., Sinzinger, E. (2008). Image Matching Using High Dynamic Range Images and Radial Feature Descriptors. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_35

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  • DOI: https://doi.org/10.1007/978-3-540-89639-5_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89638-8

  • Online ISBN: 978-3-540-89639-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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