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Representation of local geometry in the visual system

J. J. Koenderink1 and A. J. van Doorn1

(1) Department of Medical and Physiological Physics, Physics Laboratory, State University Utrecht, NL-3508 TA Utrecht, The Netherlands

Received: 2 July 1986  

Abstract  It is shown that a convolution with certain reasonable receptive field (RF) profiles yields the exact partial derivatives of the retinal illuminance blurred to a specified degree. Arbitrary concatenations of such RF profiles yield again similar ones of higher order and for a greater degree of blurring.
By replacing the illuminance with its third order jet extension we obtain position dependent geometries. It is shown how such a representation can function as the substrate for ldquopoint processorsrdquo computing geometrical features such as edge curvature. We obtain a clear dichotomy between local and multilocal visual routines. The terms of the truncated Taylor series representing the jets are partial derivatives whose corresponding RF profiles closely mimic the well known units in the primary visual cortex. Hence this description provides a novel means to understand and classify these units.
Taking the receptive field outputs as the basic input data one may devise visual routines that compute geometric features on the basis of standard differential geometry exploiting the equivalence with the local jets (partial derivatives with respect to the space coordinates).

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  1. Reisert, M. (2008) . IEEE Transactions on Image Processing 17(12)
    [CrossRef]
  2. Shi, Yonghong (2008) . IEEE Transactions on Medical Imaging 27(4)
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  3. Griffin, Lewis D. (2007) . IEEE Transactions on Pattern Analysis and Machine Intelligence 29(8)
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  4. Damerval, C. (2009) Study of a Robust Feature: The Pointwise Lipschitz Regularity. International Journal of Computer Vision
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  5. Pizer, Stephen M. (1991) Fundamental properties of medical image perception. Journal of Digital Imaging 4(1)
    [CrossRef]
  6. Lindeberg, Tony, 2008
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  7. Ravela, S., 1999
    [CrossRef]
  8. XU, Xiao-Ming (2009) The Algorithm of Descriptor Based on Locality Preserving Projections. ACTA AUTOMATICA SINICA 34(9)
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  9. Haan, Erik de (1995) Edge-curvature discriminability argues against explicit curvature detectors. Journal of the Optical Society of America A 12(2)
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  10. Gijsenij, Arjan (2008) Generalized Gamut Mapping using Image Derivative Structures for Color Constancy. International Journal of Computer Vision
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