Bioplausible Multiscale Filtering in Retinal to Cortical Processing as a Model of Computer Vision

Nasim Nematzadeh, Trent W. Lewis, David M. W. Powers

2015

Abstract

Visual illusions emerge as an attractive field of research with the discovery over the last century of a variety of deep and mysterious mechanisms of visual information processing in the human visual system. Among many classes of visual illusion relating to shape, brightness, colour and motion, “geometrical illusions” are essentially based on the misperception of orientation, size, and position. The main focus of this paper is on illusions of orientation, sometimes referred to as “tilt illusions”, where parallel lines appear not to be parallel, a straight line is perceived as a curved line, or angles where lines intersect appear larger or smaller. Although some low level and high level explanations have been proposed for geometrical tilt illusions, a systematic explanation based on model predictions of both illusion magnitude and local tilt direction is still an open issue. Here a neurophysiological model is expounded based on Difference of Gaussians implementing a classical receptive field model of retinal processing that predicts tilt illusion effects.

References

  1. Ali, H. B., Powers, D. M., 2014. "Facial Expression Recognition Based On WAPA AND OEPA FASTICA". International Journal of Artificial Intelligence & Applications, 5(3).
  2. Anderson, B. L., 1997. "A theory of illusory lightness and transparency in monocular and binocular images: The role of contour junctions". Perception-London-, 26, 419-454.
  3. Anderson, B. L., Winawer, J., 2005. "Image segmentation and lightness perception". Nature, 434(7029), 79-83.- Scission theory.
  4. Barlow, H. B., Hill, R. M., 1963. "Selective sensitivity to direction of movement in ganglion cells of the rabbit retina". Science, 139(3553), 412-412.
  5. Blakeslee, B., McCourt, M. E., 1999. "A multiscale spatial filtering account of the White effect, simultaneous brightness contrast and grating induction". Vision research, 39(26), 4361-4377.
  6. Blakeslee, B., McCourt, M. E., 2004. "A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization", Vision Research, 44, 2483-2503.
  7. Burt, P. Adelson, E., 1983. "The Lapalacian pyramid as a compact image code", IEEE Trans. Comm., vol. COM-31, pp. 532-549, Apr.
  8. Carandini, M., 2004. "Receptive fields and suppressive fields in the early visual system". The cognitive neurosciences, 3, 313-326.
  9. Cavanaugh, J. R., Bair, W., Movshon, J. A., 2002. "Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons". Journal of neurophysiology, 88(5), 2530-2546.
  10. Chao-Yi, L., Wu, L., 1994. "Extensive integration field beyond the classical receptive field of cat's striate cortical neurons-classification and tuning properties". Vision research, 34(18), 2337-2355.
  11. Daugmann, J. G., 1980. "Two-dimensional spectral analysis of cortical receptive field profile", Vision Res., vol. 20, pp. 847-856.
  12. DeValois, R. L., DeValois, K. K., 1988. "Spatial vision". New York: Oxford University Press.
  13. Enroth-Cugell, C., Robson, J.G., 1966. "The contrast sensitivity of the retinal ganglion cells of the cat", Journal of Physiology (London) 187 517-552.
  14. Field, G. D., Chichilnisky, E. J. 2007. "Information processing in the primate retina: circuitry and coding". Annu. Rev. Neurosci., 30, 1-30.
  15. Führ, H., Demaret, L., Friedrich, F., 2006. "Beyond wavelets: New image representation paradigms". Document and image compression, 7, 179-206.
  16. Fermüller, C., Malm, H., 2004. "Uncertainty in visual processes predicts geometrical optical illusions". Vision research, 44(7), 727-749.
  17. Ghosh, K. Sarkar, S. Bhaumik, K. 2007. "Understanding image structure from a new multiscale representation of higher order derivative filters". Image and Vision Computing 25(8): 1228-1238.
  18. Gilchrist, A., Kossyfidis, C., Bonato, F., Agostini, T., Cataliotti, J., Li, X., et al. 1999. "An anchoring theory of lightness perception". Psychological Review, 106, 795-834.
  19. Gregory, R. L., Heard, P., 1979. "Border locking and the Café Wall illusion". Perception, 8(4), 365-380.
  20. Grigorescu, C., Petkov, N., Westenberg, M. A., 2003. "Contour detection based on nonclassical receptive field inhibition". Image Processing, IEEE Transactions on, 12(7), 729-739.
  21. Grossberg, S., Todorovic, D., 1988. "Neural dynamics of 1-D and 2-D brightness perception: A unified model of classical and recent phenomena". Perception & Psychophysics, 43, 241-277.
  22. Hubel, D. Wiesel, T., 1962. "Receptive fields, binocular interaction and functional architecture Ain the cat's visual cortex", J. Physiol., vol. 160.
  23. Jacques, L., Duval, L., Chaux, C., Peyré, G., 2011. "A panorama on multiscale geometric representations, intertwining spatial, directional and frequency selectivity". Signal Processing, 91(12), 2699-2730.
  24. Jameson, D., 1985 . "Opponent-colours theory in the light of physiological findings". In D. Ottoson, & S. Zeki (Eds.), Central and peripheral mechanisms of colour vision (pp. 83-102). London: MacMillan.
  25. Jameson, D., Hurvich, L. M., 1989. "Essay concerning color constancy". Annual review of psychology, 40(1), 1-24.
  26. Kingdom, F. A. A., 2011. "Lightness, brightness and transparency: A quarter century of new ideas, captivating demonstrations and unrelenting controversy". Vision Research, 51, 652-673.
  27. Kitaoka, A., 2007. "Tilt illusions after Oyama (1960): A review1". Japanese Psychological Research, 49(1), 7- 19.
  28. Lourens, T., 1995. "Modelling retinal high and low contrast sensitivity filters". In From Natural to Artificial Neural Computation (pp. 61-68). Springer Berlin Heidelberg.
  29. Lowe, D. G., 1999. "Object recognition from local scaleinvariant features". Proceedings of the International Conference on Computer Vision 2. pp. 1150-1157. doi:10.1109/ICCV.1999.790410.
  30. Lindeberg, T., 2011. "Generalized Gaussian scale space axiomatics comprising linear scale-space, affine scale-space and spatio-temporal scale-space", Journal of Mathematical Imaging and Vision, Volume 40, Number 1, 36-81.
  31. Linsenmeier, R. A., Frishman, L. J., Jakiela, H. G., Enroth-Cugell, C., 1982. "Receptive field properties of X and Y cells in the cat retina derived from contrast sensitivity measurements". Vision research, 22(9), 1173-1183.
  32. Mallat, S., 1996. "Wavelets for Vision". Proceedings of the IEEE, vol 84, no. 4, april 1996.
  33. von der Malsburg, C., 1973. "Self-organization of orientation sensitive cells in the striate cortex". Kybernetik, 14(2), 85-100.
  34. Mangel, S. C., 1991. "Analysis of the horizontal cell contribution to the receptive field surround of ganglion cells in the rabbit retina". The Journal of physiology, 442(1), 211-234.
  35. Marr, D., Hildreth, E., 1980. "Theory of edge detection", Proc. of Royal Society of London B 207, 187-217.
  36. Marr, D., 1982. "Vision", W.H. Freeman and Company, New York. Zero-crossing.
  37. McCourt, M. E., 1983. "Brightness induction and the von der Malsburg illusion". Perception 12: 131-142.
  38. McGill C. A., 2014. Le cerveau à tous les niveaux. [ONLINE] Available at: http://thebrain.mcgill.ca. (Including links vision, and retina).
  39. Merry, R. J. E., Steinbuch, M., 2005. "Wavelet theory and applications". A literature study, Eindhoven University of Technology.
  40. Ninio, J., Pinna, B., 2006. "Orthogonal expansion: a neglected factor in tilt illusions". Psychologia, 49(1), 23-37.
  41. Otazu, X., Vanrell, M., Alejandro Parraga, C., 2008. "Multiresolution wavelet framework models brightness induction effects". Vision Research, 48(5), 733-751.
  42. Penacchio, O., Otazu, X., Dempere-Marco, L., 2013. "A Neurodynamical Model of Brightness Induction in V1". PloS one, 8(5), e64086.
  43. Passaglia, C. L., Enroth-Cugell, C., Troy, J. B., 2001. "Effects of remote stimulation on the mean firing rate of cat retinal ganglion cells", Journal of Neuroscience 21, 5794-5803.
  44. Powers, D. M. W., 1983. "Lateral Interaction Behaviour Derived from Neural Packing Considerations", Technical Report No 8317, Department of Computer Science, University of NSW, Australia.
  45. Rao, R. P., Ballard, D. H., 1999. "Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects". Nature neuroscience, 2(1), 79-87.
  46. Robinson, A. E., Hammon, P. S., de Sa, V. R., 2007. "Explaining brightness illusions using spatial filtering and local response normalization". Vision research, 47(12), 1631-1644.
  47. Rodieck, R. W., Stone, J., 1965. "Analysis of receptive fields of cat retinal ganglion cells", Journal of Neurophysiology 28, 833-849.
  48. Rosenfeld, A., Thurston, M., 1971. "Edge and curve detection for visual scene analysis". Computers, IEEE Transactions on, 100(5), 562-569.
  49. Shapley, R., Hugh Perry, V., 1986. "Cat and monkey retinal ganglion cells and their visual functional roles". Trends in Neurosciences, 9, 229-235.
  50. Smith, R. G., Freed, M. A., Sterling, P., 1986. "Microcircuitry of the dark-adapted cat retina: functional architecture of the rod-cone network". The Journal of neuroscience, 6(12), 3505-3517.
  51. Smith, S. W., 2003. "Digital signal processing: a practical guide for engineers and scientists". Newnes.
  52. Smith, V. C., Jin, P. Q., Pokorny, J., 2001. "The role of spatial frequency in color induction". Vision Research, 41, 1007-1021.
  53. Tanaka, H., Ohzawa, I., 2009. "Surround suppression of V1 neurons mediates orientation-based representation of high-order visual features". Journal of neurophysiology, 101(3), 1444-1462.
  54. Tani, Y., Maruya, K., Sato, T., 2006. "Reversed Café Wall illusion with missing fundamental gratings". Vision research, 46(22), 3782-3785.
  55. ter Haar Romeny, B. M., 2003. "A scale-space model for the retinal sampling. Front-End Vision and MultiScale Image Analysis". Multi-Scale Computer Vision Theory and Applications, written in Mathematics, 167-177.
  56. Wei, H., Wang, Z. Y., Zuo, Q. S., 2012. "A model of image representation based on non-classical receptive fields". In Advances in Neural Networks-ISNN 2012 (pp. 297-306). Springer Berlin Heidelberg.
  57. Wei, H., Zuo, Q., Lang, B., 2011. "Multi-scale image analysis based on non-classical receptive field mechanism". In Neural Information Processing (pp. 601-610). Springer Berlin Heidelberg.
  58. Westheimer, G., 2007. "Irradiation, border location, and the shifted-chessboard pattern". Perception, 36(4), 483.
  59. Witkin, A. P., 1983. "Scale-space filtering", in: Proceedings of International Joint Conferences on Artificial Intelligence, Karlsruhe, pp. 1019-1022.
  60. Xie, X., Lam, K. M., Zhao, H., Dai, Q., 2008. "Efficient rotation-and scale-invariant texture classification method based on Gabor wavelets". Journal of Electronic Imaging, 17(4), 043026-043026.
  61. Young, R.A., 1985. "The Gaussian derivative theory of spatial vision: analysis of cortical cell receptive field line weighting profiles". General Motors Research Publication GMR-4920.
  62. Young, R. A., 1987. "The Gaussian derivative model for spatial vision: I. Retinal mechanisms", Spatial Vision 2, 273-293.
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Paper Citation


in Harvard Style

Nematzadeh N., W. Lewis T. and M. W. Powers D. (2015). Bioplausible Multiscale Filtering in Retinal to Cortical Processing as a Model of Computer Vision . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-074-1, pages 305-316. DOI: 10.5220/0005186203050316


in Bibtex Style

@conference{icaart15,
author={Nasim Nematzadeh and Trent W. Lewis and David M. W. Powers},
title={Bioplausible Multiscale Filtering in Retinal to Cortical Processing as a Model of Computer Vision},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2015},
pages={305-316},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005186203050316},
isbn={978-989-758-074-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Bioplausible Multiscale Filtering in Retinal to Cortical Processing as a Model of Computer Vision
SN - 978-989-758-074-1
AU - Nematzadeh N.
AU - W. Lewis T.
AU - M. W. Powers D.
PY - 2015
SP - 305
EP - 316
DO - 10.5220/0005186203050316