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Orientation Contrast Detection in Space-Variant Images

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Biologically Motivated Computer Vision (BMCV 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1811))

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Abstract

In order to appropriately act in a dynamic environment, any biological or artificial agent needs to be able to locate object boundaries and use them to segregate the objects from each other and from the background. Since contrasts in features such as luminance, color, texture, motion and stereo may signal object boundaries, locations of high feature contrast should summon an agent’s attention. In this paper, we present an orientation contrast detection scheme, and show how it can be adapted to work on a cortical data format modeled after the retino-cortical remapping of the visual field in primates. Working on this cortical image is attractive because it yields a high resolution, wide field of view, and a significant data reduction, allowing real-time execution of image processing operations on standard PC hardware. We show how the disadvantages of the cortical image format, namely curvilinear coordinates and the hemispheric divide, can be dealt with by angle correction and filling-in of hemispheric borders.

This research was performed in the collaborative research center devoted to the “Integration of symbolic and sub-symbolic information processing in adaptive sensorymotor systems” (SFB-527) at the University of Ulm, funded by the German Science Foundation (DFG).

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Author information

Authors and Affiliations

  1. Dept. of Neural Information Processing, University of Ulm, 89069, Ulm, Germany

    Gregory Baratoff, Ralph Schönfelder, Ingo Ahrns & Heiko Neumann

Authors
  1. Gregory Baratoff
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  2. Ralph Schönfelder
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  3. Ingo Ahrns
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  4. Heiko Neumann
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Editor information

Editors and Affiliations

  1. Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-ku, Seoul, 136-701, Korea

    Seong-Whan Lee

  2. Max-Planck-Institute for Biological Cybernetics, Spemannstr. 38, 72076, Tübingen, Germany

    Heinrich H. Bülthoff

  3. Department of Brain and Cognitive Sciences Artificial Intelligence Laboratory, E25-218, Massachusetts Institute of Technology, 45 Carleton Street, Cambridge, MA, 02142, USA

    Tomaso Poggio

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© 2000 Springer-Verlag Berlin Heidelberg

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Baratoff, G., Schönfelder, R., Ahrns, I., Neumann, H. (2000). Orientation Contrast Detection in Space-Variant Images. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_56

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  • DOI: https://doi.org/10.1007/3-540-45482-9_56

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67560-0

  • Online ISBN: 978-3-540-45482-3

  • eBook Packages: Springer Book Archive

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