OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 7, Iss. 5 — May. 1, 1990
  • pp: 923–932

Preattentive texture discrimination with early vision mechanisms

Jitendra Malik and Pietro Perona  »View Author Affiliations

JOSA A, Vol. 7, Issue 5, pp. 923-932 (1990)

View Full Text Article

Enhanced HTML    Acrobat PDF (2190 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



We present a model of human preattentive texture perception. This model consists of three stages: (1) convolution of the image with a bank of even-symmetric linear filters followed by half-wave rectification to give a set of responses modeling outputs of V1 simple cells, (2) inhibition, localized in space, within and among the neural-response profiles that results in the suppression of weak responses when there are strong responses at the same or nearby locations, and (3) texture-boundary detection by using wide odd-symmetric mechanisms. Our model can predict the salience of texture boundaries in any arbitrary gray-scale image. A computer implementation of this model has been tested on many of the classic stimuli from psychophysical literature. Quantitative predictions of the degree of discriminability of different texture pairs match well with experimental measurements of discriminability in human observers.

© 1990 Optical Society of America

Original Manuscript: July 7, 1989
Manuscript Accepted: December 28, 1989
Published: May 1, 1990

Jitendra Malik and Pietro Perona, "Preattentive texture discrimination with early vision mechanisms," J. Opt. Soc. Am. A 7, 923-932 (1990)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. B. Julesz, “Textons, the elements of texture perception and their interactions,” Nature (London) 290, 91–97 (1981). [CrossRef]
  2. J. Bergen, B. Julesz, “Rapid discrimination of visual patterns,” IEEE Trans. Syst. Man Cybern. 13, 857–863 (1983). [CrossRef]
  3. B. Julesz, “Texton gradients: the texton theory revisited,” Biol. Cybern. 54, 245–251 (1986). [CrossRef] [PubMed]
  4. J. Beck, “Similarity grouping and peripheral discriminability under uncertainty,” Am. J. Psychol. 85, 1–19 (1972). [CrossRef] [PubMed]
  5. J. Beck, “Textural segmentation,” in Organization and Representation in Perception, J. Beck, ed. (Erlbaum, Hillsdale, N.J., 1982).
  6. J. Beck, K. Prazdny, A. Rosenfeld, Human and Machine Vision(Academic, New York, 1983), pp. 1–38.
  7. H. Voorhees, T. Poggio, “Computing texture boundaries from images,” Nature (London) 333, 364–367 (1988). [CrossRef]
  8. J. Enns, “Seeing textons in context,” Percept. Psychophys. 39, 143–147 (1986). [CrossRef] [PubMed]
  9. J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segmentation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987). [CrossRef]
  10. R. Gurnsey, R. Browse, “Micropattern properties and presentation conditions influencing visual texture discrimination,” Percept. Psychophys. 41, 239–252 (1987). [CrossRef] [PubMed]
  11. T. Caelli, “Three processing characteristics of visual texture segmentation,” Spatial Vision 1, 19–30 (1985). [CrossRef] [PubMed]
  12. J. Coggins, A. K. Jain, “A spatial filtering approach to texture analysis,” Pattern Recogn. Lett. 3, 195–203 (1985). [CrossRef]
  13. M. Turner, “Texture discrimination by gabor functions,” Biol. Cybern. 55, 71–82 (1986). [PubMed]
  14. J. Bergen, E. Adelson, “Early vision and texture perception,” Nature (London) 333, 363–364 (1988). [CrossRef]
  15. A. Sutter, J. Beck, N. Graham, “Contrast and spatial variables in texture segregation: testing a simple spatial-frequency channels model,” Percept. Psychophys. 46, 312–332 (1989). [CrossRef] [PubMed]
  16. I. Fogel, D. Sagi, “Gabor filters as texture discriminators,” Biol. Cybern. 61, 103–113 (1989). [CrossRef]
  17. B. J. Kröse, A Description of Visual Structure, Ph.D. dissertation (Delft University of Technology, Delft, The Netherlands, 1986).
  18. B. Julesz, B. Kröse, “Features and spatial filters,” Nature (London) 333, 302–303 (1988). [CrossRef]
  19. B. Julesz, AT&T Bell Laboratories, Murray Hill, New Jersey 07974 (personal communication).
  20. H. Spitzer, S. Hochstein, “Simple- and complex-cell response dependences on stimulation parameters, and A complex cell receptive-field model,” J. Neurophysiol. 53, 1244–1286 (1985). [PubMed]
  21. H. C. Nothdurft, “Sensitivity for structure gradient for texture discrimination tasks,” Vision Res. 25, 1957–1968 (1985). [CrossRef]
  22. A. Treisman, “Preattentive processing in vision,” Comput. Vision Graphics Image Process. 31, 156–177 (1985). [CrossRef]
  23. P. R. Kube, On Image Texture, Ph.D. dissertation (University of California, Berkeley, Berkeley, Calif., 1988).
  24. J. D. Daugman, “Two dimensional spectral analysis of cortical receptive field profiles,” Vision Res. 20, 847–856 (1980). [CrossRef]
  25. R. Young, “The Gaussian derivative theory of spatial vision: analysis of cortical cell receptive field line-weighting profiles,” Tech. Rep. GMR-4920 (General Motors Research, Warren, Mich., 1985).
  26. A. Parker, M. J. Hawken, “Two-dimensional spatial structure of receptive fields in monkey striate cortex,” J. Opt. Soc. Am. A 5, 598–605 (1988). [CrossRef] [PubMed]
  27. D. Field, J. Nachmias, “Phase reversal discrimination,” J. Vis. Res. 24, 333–340 (1984). [CrossRef]
  28. D. Burr, C. Morrone, D. Spinelli, “Evidence of edge and bar detectors in human vision,” Vision Res. 29, 419–431 (1989). [CrossRef]
  29. We have used a linear sampling of the frequency space instead of the more common logarithmic sampling. The way we combine the output of the different channels makes this choice immaterial, provided that the sampling is dense enough.
  30. H. Voorhees, “Finding texture boundaries in images,” Tech. Rep. 968 (Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Cambridge, Mass., 1987).
  31. B. Julesz, E. N. Gilbert, J. D. Victor, “Visual discrimination of textures with identical third order statistics,” Biol. Cybern. 31, 137–140 (1978). [CrossRef] [PubMed]
  32. R. Shapley, C. Enroth-Cugell, “Visual adaptation and retinal gain controls,” Prog. Retinal Res. 4, 263–347 (1984). [CrossRef]
  33. N. Graham, J. Beck, A. Sutter, “Two nonlinearities in texture segregation,” Invest. Ophtalmol. Vis. Sci. 30, 161 (1989).
  34. D. Albrecht, D. Hamilton, “Striate cortex of monkey and cat: contrast response function,” J. Neurophysiol. 48, 217–237 (1982). [PubMed]
  35. K. Toyama, M. Kimura, K. Tanaka, “Organization of cat visual cortex as investigated by cross-correlation techniques,” J. Neurophysiol. 46, 202–214 (1981). [PubMed]
  36. K. De Valois, R. Tootell, “Spatial-frequency-specific inhibition in car striate cortex cells,” J. Physiol. 336, 359–376 (1983).
  37. A. M. Sillito, P. C. Murphy, Neurotransmitters and Cortical Function: From Molecules to Mind (Plenum, New York, 1988), Chap. 11.
  38. D. Tolhurst, “Adaptation to square wave gratings: inhibition between spatial frequency channels in the human visual system,” J. Physiol. 226, 231–248 (1972). [PubMed]
  39. A. B. Bonds, “Role of inhibition in the specification of orientation selectivity of cells in the car striate cortex,” Visual Neurosci. 2, 41–55 (1989). [CrossRef]
  40. I. Rentschler, M. Hubner, T. Caelli, “On the discrimination of compound Gabor signals and textures,” Vision Res. 28, 279–291 (1988). [CrossRef] [PubMed]
  41. Data are from Ref. 17. The tabulated data correspond to δtb(Table 3.1, p. 39; stimulus onset asynchrony, 320).
  42. B. Kröse, “Local structure analyzers as determinants of preattentive pattern discrimination,” Biol. Cybern. 55, 289–298 (1987). [CrossRef] [PubMed]
  43. Data are from Ref. 10. The tabulated data correspond to mean overall discriminability (pairs 1.1, 1.2, 1.3, 3.1) averaged over foreground/background and different stimulus durations.
  44. J. Malik, P. Perona, “A computational model of texture perception,” Tech. Rep. UCB/CSD 89/491 (Computer Science Division, University of California, Berkeley, Berkeley, Calif., 1989).
  45. B. Julesz, AT&T Bell Laboratories, Murray Hill, New Jersey 07974 (personal communication).
  46. B. Rubenstein, D. Sagi, “Texture variability across the orientation spectrum can yield asymmetry in texture discrimination,” Perception 18, 517 (1989).
  47. J. Malik, P. Perona, “A computational model of human texture perception,” Invest. Ophthalmol. Vis. Sci. 30, 161 (1989).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited