Abstract

Texture-discimination tasks reveal a pronounced performance asymmetry depending on which texture represents the foreground region (small area) and which represents the ground (large area). This asymmetry implies that some global processes are involved in the segmentation process. We examined this problem within the context of the texture-segmentation algorithm, assuming two filtering stages. The first stage uses spatial frequency and orientation-selective (Gabor) filters, whereas the second stage is formed by low-resolution edge-detection filters. The presence and location of texture borders are indicated by significant responses in the second stage. Spurious texture borders may occur owing to textural local variabilities (such as orientation randomization), which are enhanced by the first stage. We suggest that these spurious borders act as background noise and thus limit performance in texture-discrimination tasks. The noise level depends on which texture occupies the ground in the display. We tested this model on numerous pairs of textures and found remarkably good correlation with human performance. A prediction of the model, namely, that discrimination asymmetry will be reduced when textural elements have identical orientation, was tested psychophysically and confirmed.

© 1990 Optical Society of America

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  1. R. Gurnsey, R. Browse, “Micropattern properties and presentation conditions influencing visual texture discrimination,” Percept. Psychophys. 41, 239–252 (1987).
    [CrossRef] [PubMed]
  2. J. Beck, “Textural segmentation,” in Organization and Representation in Perception, J. Beck, ed. (Erlbaum, Hillsdale, N.J., 1982).
  3. H. C. Nothdurft, “Sensitivity for structure gradient in texture discrimination task,” Vision Res. 25, 1957–1968 (1985).
    [CrossRef]
  4. D. Sagi, B. Julesz, “‘Where’ and ‘what’ in vision,” Science 228, 1217–1219 (1985).
    [CrossRef] [PubMed]
  5. D. Sagi, B. Julesz, “Short-range limitation on detection of feature differences,” Spatial Vision 2, 39–49 (1987).
    [CrossRef] [PubMed]
  6. A. Treisman, “Preattentive processing in vision,” Comput. Vision Graphics Image Process. 31, 156–177 (1985).
    [CrossRef]
  7. A. Treisman, “Features and objects in visual processing,” Sci. Am. 255, 106–125 (1986).
    [CrossRef]
  8. R. Gurnsey, R. Browse, “Aspects of visual texture discrimination,” in Computational Processes in Human Vision: An Interdisciplinary Perspective, Z. Pylyshyn, ed. (Ablex, Norwood, N.J., 1988).
  9. A. Treisman, S. Gormican, “Feature analysis in early vision: evidence from search asymmetries,” Psychol. Rev. 95, 15–48 (1988).
    [CrossRef] [PubMed]
  10. A. Treisman, J. Souther, “Search asymmetry: a diagnostic for preattentive processing of separable features,” J. Exp. Psychol. 114, 285–310 (1985).
    [CrossRef]
  11. B. Julesz, “A brief outline of the texton theory of human vision,” Trends Neurosci. 7, 41–45 (1984).
    [CrossRef]
  12. B. Julesz, “Texton gradients: the texton theory revisited,” Biol. Cybern. 54, 245–251 (1986).
    [CrossRef] [PubMed]
  13. I. Fogel, D. Sagi, “Gabor filters as texture discriminator,” Biol. Cybern. 61, 103–113 (1989).
    [CrossRef]
  14. J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segregation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987).
    [CrossRef]
  15. T. M. Caelli, “Three processing characteristics of visual texture segmentation,” Spatial Vision 1, 19–30 (1985).
    [CrossRef] [PubMed]
  16. J. D. Daugman, D. M. Kammen, “Pure orientation filtering: a scale-invariant image-processing tool for perception research and data compression,” Behav. Res. Meth. Instrum. Comput. 18, 559–564 (1986).
    [CrossRef]
  17. M. R. Turner, “Texture discrimination by Gabor functions,” Biol. Cybern. 55, 71–82 (1986).
    [PubMed]
  18. B. Julesz, “Visual pattern discrimination,” IRE Trans. Inf. Theory 8, 84–92 (1962).
    [CrossRef]
  19. B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
    [CrossRef]
  20. D. A. Pollen, S. F. Ronner, “Visual cortical neurons as localized spatial frequency filters,” IEEE Trans. Syst. Man Cybern. SMC-13, 907–916 (1983).
    [CrossRef]
  21. F. W. Campbell, J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. (London) 197, 551–566 (1968).
  22. J. Daugman, “Two dimensional spectral analysis of cortical receptive field profiles,” Vision Res. 25, 671–684 (1980).
  23. D. Sagi, “The combination of spatial frequency and orientation is effortlessly perceived,” Percept. Psychophys. 43, 601–603 (1988).
    [CrossRef] [PubMed]
  24. A. B. Watson, J. G. Robson, “Discrimination at threshold: labeled detectors in human vision,” Vision Res. 21, 1115–1122 (1981).
    [CrossRef]
  25. H. R. Wilson, J. R. Bergen, “A four mechanism model for threshold spatial vision,” Vision Res. 19, 19–32 (1979).
    [CrossRef] [PubMed]
  26. D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.
  27. C. Chubb, G. Sperling, J. Solomon, “Texture interactions determine apparent lightness,” Proc. Natl. Acad. Sci. USA 86, 9631–9635 (1989).
    [CrossRef]
  28. M. S. Landy, J. R. Bergen, “Texture segregation for filtered noise patterns,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 160 (1989).
  29. D. Sagi, “Detection of an orientation singularity in Gabor textures: effect of signal density and spatial-frequency,” Vision Res. (to be published)2848921.
  30. D. Sagi, S. Hochstein, “Lateral inhibition between spatially adjacent spatial frequency channels?” Percept. Psychophys. 37, 315–322 (1985).
    [CrossRef] [PubMed]
  31. J. R. Bergen, E. H. Adelson, “Early vision and texture perception,” Nature (London) 333, 363–364 (1988).
    [CrossRef]
  32. J. Malik, P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. 7, 923–932 (1990).
    [CrossRef]
  33. H. Voorees, T. Poggio, “Computing texture boundaries from images,” Nature (London) 333, 364–367 (1988).
    [CrossRef]
  34. D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).
  35. H. R. Wilson, D. J. Gelb, “Modified line-element theory for spatial-frequency and width discrimination,” J. Opt. Soc. Am. A 1, 124–131 (1984).
    [CrossRef] [PubMed]
  36. A. B. Watson, J. Nachmias, “Patterns of temporal interaction in the detection of gratings,” Vision Res. 17, 893–902 (1977).
    [CrossRef] [PubMed]
  37. R. Gurnsey, Department of Psychology, University of Western Toronto, London, Ontario N6A 5C2, Canada (personal communication, 1989).
  38. B. Julesz, “Spatial nonlinearities in the visual perception of textures with identical power spectra,” Philos. Trans. R. Soc. London Ser. B 290, 83–94 (1980).
    [CrossRef]
  39. J. Enns, “Seeing textons in context,” Percept. Psychophys. 39, 143–147 (1986).
    [CrossRef] [PubMed]
  40. H. C. Nothdurft, “Texton segregation by associated differences in global and local luminance distribution,” Proc. R. Soc. London Ser. B 239, 295–320 (1990).
    [CrossRef]
  41. O. Smikt, Department of Applied Mathematics, The Weizmann Institute of Science, Rehovot 76100, Israel (personal communication, 1988).

1990 (2)

J. Malik, P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. 7, 923–932 (1990).
[CrossRef]

H. C. Nothdurft, “Texton segregation by associated differences in global and local luminance distribution,” Proc. R. Soc. London Ser. B 239, 295–320 (1990).
[CrossRef]

1989 (3)

C. Chubb, G. Sperling, J. Solomon, “Texture interactions determine apparent lightness,” Proc. Natl. Acad. Sci. USA 86, 9631–9635 (1989).
[CrossRef]

M. S. Landy, J. R. Bergen, “Texture segregation for filtered noise patterns,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 160 (1989).

I. Fogel, D. Sagi, “Gabor filters as texture discriminator,” Biol. Cybern. 61, 103–113 (1989).
[CrossRef]

1988 (4)

A. Treisman, S. Gormican, “Feature analysis in early vision: evidence from search asymmetries,” Psychol. Rev. 95, 15–48 (1988).
[CrossRef] [PubMed]

D. Sagi, “The combination of spatial frequency and orientation is effortlessly perceived,” Percept. Psychophys. 43, 601–603 (1988).
[CrossRef] [PubMed]

H. Voorees, T. Poggio, “Computing texture boundaries from images,” Nature (London) 333, 364–367 (1988).
[CrossRef]

J. R. Bergen, E. H. Adelson, “Early vision and texture perception,” Nature (London) 333, 363–364 (1988).
[CrossRef]

1987 (3)

R. Gurnsey, R. Browse, “Micropattern properties and presentation conditions influencing visual texture discrimination,” Percept. Psychophys. 41, 239–252 (1987).
[CrossRef] [PubMed]

D. Sagi, B. Julesz, “Short-range limitation on detection of feature differences,” Spatial Vision 2, 39–49 (1987).
[CrossRef] [PubMed]

J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segregation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987).
[CrossRef]

1986 (5)

J. D. Daugman, D. M. Kammen, “Pure orientation filtering: a scale-invariant image-processing tool for perception research and data compression,” Behav. Res. Meth. Instrum. Comput. 18, 559–564 (1986).
[CrossRef]

M. R. Turner, “Texture discrimination by Gabor functions,” Biol. Cybern. 55, 71–82 (1986).
[PubMed]

A. Treisman, “Features and objects in visual processing,” Sci. Am. 255, 106–125 (1986).
[CrossRef]

B. Julesz, “Texton gradients: the texton theory revisited,” Biol. Cybern. 54, 245–251 (1986).
[CrossRef] [PubMed]

J. Enns, “Seeing textons in context,” Percept. Psychophys. 39, 143–147 (1986).
[CrossRef] [PubMed]

1985 (6)

D. Sagi, S. Hochstein, “Lateral inhibition between spatially adjacent spatial frequency channels?” Percept. Psychophys. 37, 315–322 (1985).
[CrossRef] [PubMed]

A. Treisman, J. Souther, “Search asymmetry: a diagnostic for preattentive processing of separable features,” J. Exp. Psychol. 114, 285–310 (1985).
[CrossRef]

A. Treisman, “Preattentive processing in vision,” Comput. Vision Graphics Image Process. 31, 156–177 (1985).
[CrossRef]

H. C. Nothdurft, “Sensitivity for structure gradient in texture discrimination task,” Vision Res. 25, 1957–1968 (1985).
[CrossRef]

D. Sagi, B. Julesz, “‘Where’ and ‘what’ in vision,” Science 228, 1217–1219 (1985).
[CrossRef] [PubMed]

T. M. Caelli, “Three processing characteristics of visual texture segmentation,” Spatial Vision 1, 19–30 (1985).
[CrossRef] [PubMed]

1984 (2)

1983 (1)

D. A. Pollen, S. F. Ronner, “Visual cortical neurons as localized spatial frequency filters,” IEEE Trans. Syst. Man Cybern. SMC-13, 907–916 (1983).
[CrossRef]

1981 (1)

A. B. Watson, J. G. Robson, “Discrimination at threshold: labeled detectors in human vision,” Vision Res. 21, 1115–1122 (1981).
[CrossRef]

1980 (2)

B. Julesz, “Spatial nonlinearities in the visual perception of textures with identical power spectra,” Philos. Trans. R. Soc. London Ser. B 290, 83–94 (1980).
[CrossRef]

J. Daugman, “Two dimensional spectral analysis of cortical receptive field profiles,” Vision Res. 25, 671–684 (1980).

1979 (1)

H. R. Wilson, J. R. Bergen, “A four mechanism model for threshold spatial vision,” Vision Res. 19, 19–32 (1979).
[CrossRef] [PubMed]

1977 (1)

A. B. Watson, J. Nachmias, “Patterns of temporal interaction in the detection of gratings,” Vision Res. 17, 893–902 (1977).
[CrossRef] [PubMed]

1973 (1)

B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
[CrossRef]

1968 (1)

F. W. Campbell, J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. (London) 197, 551–566 (1968).

1962 (1)

B. Julesz, “Visual pattern discrimination,” IRE Trans. Inf. Theory 8, 84–92 (1962).
[CrossRef]

Adelson, E. H.

J. R. Bergen, E. H. Adelson, “Early vision and texture perception,” Nature (London) 333, 363–364 (1988).
[CrossRef]

Beck, J.

J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segregation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987).
[CrossRef]

J. Beck, “Textural segmentation,” in Organization and Representation in Perception, J. Beck, ed. (Erlbaum, Hillsdale, N.J., 1982).

Bergen, J. R.

M. S. Landy, J. R. Bergen, “Texture segregation for filtered noise patterns,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 160 (1989).

J. R. Bergen, E. H. Adelson, “Early vision and texture perception,” Nature (London) 333, 363–364 (1988).
[CrossRef]

H. R. Wilson, J. R. Bergen, “A four mechanism model for threshold spatial vision,” Vision Res. 19, 19–32 (1979).
[CrossRef] [PubMed]

Browse, R.

R. Gurnsey, R. Browse, “Micropattern properties and presentation conditions influencing visual texture discrimination,” Percept. Psychophys. 41, 239–252 (1987).
[CrossRef] [PubMed]

R. Gurnsey, R. Browse, “Aspects of visual texture discrimination,” in Computational Processes in Human Vision: An Interdisciplinary Perspective, Z. Pylyshyn, ed. (Ablex, Norwood, N.J., 1988).

Caelli, T. M.

T. M. Caelli, “Three processing characteristics of visual texture segmentation,” Spatial Vision 1, 19–30 (1985).
[CrossRef] [PubMed]

Campbell, F. W.

F. W. Campbell, J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. (London) 197, 551–566 (1968).

Chubb, C.

C. Chubb, G. Sperling, J. Solomon, “Texture interactions determine apparent lightness,” Proc. Natl. Acad. Sci. USA 86, 9631–9635 (1989).
[CrossRef]

Daugman, J.

J. Daugman, “Two dimensional spectral analysis of cortical receptive field profiles,” Vision Res. 25, 671–684 (1980).

Daugman, J. D.

J. D. Daugman, D. M. Kammen, “Pure orientation filtering: a scale-invariant image-processing tool for perception research and data compression,” Behav. Res. Meth. Instrum. Comput. 18, 559–564 (1986).
[CrossRef]

DeYoe, E. A.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Enns, J.

J. Enns, “Seeing textons in context,” Percept. Psychophys. 39, 143–147 (1986).
[CrossRef] [PubMed]

Fogel, I.

I. Fogel, D. Sagi, “Gabor filters as texture discriminator,” Biol. Cybern. 61, 103–113 (1989).
[CrossRef]

Fox, J.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Frisch, H. L.

B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
[CrossRef]

Gelb, D. J.

Gilbert, E. N.

B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
[CrossRef]

Gormican, S.

A. Treisman, S. Gormican, “Feature analysis in early vision: evidence from search asymmetries,” Psychol. Rev. 95, 15–48 (1988).
[CrossRef] [PubMed]

Green, D. M.

D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

Gurnsey, R.

R. Gurnsey, R. Browse, “Micropattern properties and presentation conditions influencing visual texture discrimination,” Percept. Psychophys. 41, 239–252 (1987).
[CrossRef] [PubMed]

R. Gurnsey, R. Browse, “Aspects of visual texture discrimination,” in Computational Processes in Human Vision: An Interdisciplinary Perspective, Z. Pylyshyn, ed. (Ablex, Norwood, N.J., 1988).

R. Gurnsey, Department of Psychology, University of Western Toronto, London, Ontario N6A 5C2, Canada (personal communication, 1989).

Hochstein, S.

D. Sagi, S. Hochstein, “Lateral inhibition between spatially adjacent spatial frequency channels?” Percept. Psychophys. 37, 315–322 (1985).
[CrossRef] [PubMed]

Ivry, R.

J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segregation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987).
[CrossRef]

Julesz, B.

D. Sagi, B. Julesz, “Short-range limitation on detection of feature differences,” Spatial Vision 2, 39–49 (1987).
[CrossRef] [PubMed]

B. Julesz, “Texton gradients: the texton theory revisited,” Biol. Cybern. 54, 245–251 (1986).
[CrossRef] [PubMed]

D. Sagi, B. Julesz, “‘Where’ and ‘what’ in vision,” Science 228, 1217–1219 (1985).
[CrossRef] [PubMed]

B. Julesz, “A brief outline of the texton theory of human vision,” Trends Neurosci. 7, 41–45 (1984).
[CrossRef]

B. Julesz, “Spatial nonlinearities in the visual perception of textures with identical power spectra,” Philos. Trans. R. Soc. London Ser. B 290, 83–94 (1980).
[CrossRef]

B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
[CrossRef]

B. Julesz, “Visual pattern discrimination,” IRE Trans. Inf. Theory 8, 84–92 (1962).
[CrossRef]

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Kammen, D. M.

J. D. Daugman, D. M. Kammen, “Pure orientation filtering: a scale-invariant image-processing tool for perception research and data compression,” Behav. Res. Meth. Instrum. Comput. 18, 559–564 (1986).
[CrossRef]

Knierim, J.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Landy, M. S.

M. S. Landy, J. R. Bergen, “Texture segregation for filtered noise patterns,” Invest. Ophthalmol. Vis. Sci. Suppl. 30, 160 (1989).

Malik, J.

J. Malik, P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. 7, 923–932 (1990).
[CrossRef]

Nachmias, J.

A. B. Watson, J. Nachmias, “Patterns of temporal interaction in the detection of gratings,” Vision Res. 17, 893–902 (1977).
[CrossRef] [PubMed]

Nothdurft, H. C.

H. C. Nothdurft, “Texton segregation by associated differences in global and local luminance distribution,” Proc. R. Soc. London Ser. B 239, 295–320 (1990).
[CrossRef]

H. C. Nothdurft, “Sensitivity for structure gradient in texture discrimination task,” Vision Res. 25, 1957–1968 (1985).
[CrossRef]

Olavarria, J.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Perona, P.

J. Malik, P. Perona, “Preattentive texture discrimination with early vision mechanisms,” J. Opt. Soc. Am. 7, 923–932 (1990).
[CrossRef]

Poggio, T.

H. Voorees, T. Poggio, “Computing texture boundaries from images,” Nature (London) 333, 364–367 (1988).
[CrossRef]

Pollen, D. A.

D. A. Pollen, S. F. Ronner, “Visual cortical neurons as localized spatial frequency filters,” IEEE Trans. Syst. Man Cybern. SMC-13, 907–916 (1983).
[CrossRef]

Robson, J. G.

A. B. Watson, J. G. Robson, “Discrimination at threshold: labeled detectors in human vision,” Vision Res. 21, 1115–1122 (1981).
[CrossRef]

F. W. Campbell, J. G. Robson, “Application of Fourier analysis to the visibility of gratings,” J. Physiol. (London) 197, 551–566 (1968).

Ronner, S. F.

D. A. Pollen, S. F. Ronner, “Visual cortical neurons as localized spatial frequency filters,” IEEE Trans. Syst. Man Cybern. SMC-13, 907–916 (1983).
[CrossRef]

Sagi, D.

I. Fogel, D. Sagi, “Gabor filters as texture discriminator,” Biol. Cybern. 61, 103–113 (1989).
[CrossRef]

D. Sagi, “The combination of spatial frequency and orientation is effortlessly perceived,” Percept. Psychophys. 43, 601–603 (1988).
[CrossRef] [PubMed]

D. Sagi, B. Julesz, “Short-range limitation on detection of feature differences,” Spatial Vision 2, 39–49 (1987).
[CrossRef] [PubMed]

D. Sagi, B. Julesz, “‘Where’ and ‘what’ in vision,” Science 228, 1217–1219 (1985).
[CrossRef] [PubMed]

D. Sagi, S. Hochstein, “Lateral inhibition between spatially adjacent spatial frequency channels?” Percept. Psychophys. 37, 315–322 (1985).
[CrossRef] [PubMed]

D. Sagi, “Detection of an orientation singularity in Gabor textures: effect of signal density and spatial-frequency,” Vision Res. (to be published)2848921.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Shepp, L. A.

B. Julesz, H. L. Frisch, E. N. Gilbert, L. A. Shepp, “Inability of humans to discriminate between visual textures that agree in second-order statistics,” Biol. Cybern. 31, 137–140 (1973).
[CrossRef]

Smikt, O.

O. Smikt, Department of Applied Mathematics, The Weizmann Institute of Science, Rehovot 76100, Israel (personal communication, 1988).

Solomon, J.

C. Chubb, G. Sperling, J. Solomon, “Texture interactions determine apparent lightness,” Proc. Natl. Acad. Sci. USA 86, 9631–9635 (1989).
[CrossRef]

Souther, J.

A. Treisman, J. Souther, “Search asymmetry: a diagnostic for preattentive processing of separable features,” J. Exp. Psychol. 114, 285–310 (1985).
[CrossRef]

Sperling, G.

C. Chubb, G. Sperling, J. Solomon, “Texture interactions determine apparent lightness,” Proc. Natl. Acad. Sci. USA 86, 9631–9635 (1989).
[CrossRef]

Sutter, A.

J. Beck, A. Sutter, R. Ivry, “Spatial frequency channels and perceptual grouping in texture segregation,” Comput. Vision Graphics Image Process. 37, 299–325 (1987).
[CrossRef]

Swets, J. A.

D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

Treisman, A.

A. Treisman, S. Gormican, “Feature analysis in early vision: evidence from search asymmetries,” Psychol. Rev. 95, 15–48 (1988).
[CrossRef] [PubMed]

A. Treisman, “Features and objects in visual processing,” Sci. Am. 255, 106–125 (1986).
[CrossRef]

A. Treisman, J. Souther, “Search asymmetry: a diagnostic for preattentive processing of separable features,” J. Exp. Psychol. 114, 285–310 (1985).
[CrossRef]

A. Treisman, “Preattentive processing in vision,” Comput. Vision Graphics Image Process. 31, 156–177 (1985).
[CrossRef]

Turner, M. R.

M. R. Turner, “Texture discrimination by Gabor functions,” Biol. Cybern. 55, 71–82 (1986).
[PubMed]

Van Essen, D. C.

D. C. Van Essen, E. A. DeYoe, J. Olavarria, J. Knierim, J. Fox, D. Sagi, B. Julesz, “Neural responses to static and moving texture patterns in visual cortex of the macaque monkey,” in Neutral Mechanisms of Visual Perception, D. M. K. Lam, C. Gilbert, eds. (Portfolio, The Woodlands, Tex., 1989), pp. 137–154.

Voorees, H.

H. Voorees, T. Poggio, “Computing texture boundaries from images,” Nature (London) 333, 364–367 (1988).
[CrossRef]

Watson, A. B.

A. B. Watson, J. G. Robson, “Discrimination at threshold: labeled detectors in human vision,” Vision Res. 21, 1115–1122 (1981).
[CrossRef]

A. B. Watson, J. Nachmias, “Patterns of temporal interaction in the detection of gratings,” Vision Res. 17, 893–902 (1977).
[CrossRef] [PubMed]

Wilson, H. R.

Behav. Res. Meth. Instrum. Comput. (1)

J. D. Daugman, D. M. Kammen, “Pure orientation filtering: a scale-invariant image-processing tool for perception research and data compression,” Behav. Res. Meth. Instrum. Comput. 18, 559–564 (1986).
[CrossRef]

Biol. Cybern. (4)

M. R. Turner, “Texture discrimination by Gabor functions,” Biol. Cybern. 55, 71–82 (1986).
[PubMed]

B. Julesz, “Texton gradients: the texton theory revisited,” Biol. Cybern. 54, 245–251 (1986).
[CrossRef] [PubMed]

I. Fogel, D. Sagi, “Gabor filters as texture discriminator,” Biol. Cybern. 61, 103–113 (1989).
[CrossRef]

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Figures (9)

Fig. 1
Fig. 1

Example of asymmetry. Visual examination shows ┌’s in the foreground (bottom half) as more salient.

Fig. 2
Fig. 2

Gabor filter texture energies, T(λ, θ), of + and ┌ for different wavelengths and orientations. Notice that, for large wavelengths, element ┌ has greater energy variability across the orientation spectrum.

Fig. 3
Fig. 3

Computer simulation of texture segmentation. The stimulus (a) is acted on by even and odd Gabor filters having an orientation of 72° to produce an energy map (Gabor patch also shown) (b). This image is in turn smoothed by a Gaussian filter (c), and finally the Gaussian image is thresholded and edge detection is performed (d). Notice the spurious clusters caused by the ┌’s in the background.

Fig. 4
Fig. 4

Same as Fig. 3 except with ┌’s in the foreground. Notice the relatively less noisy background caused by the +’s having limited orientational variability.

Fig. 5
Fig. 5

Correlation between the psychophysical results of Gurnsey and Browse1 (histogram) and the predictions of the model (circles). The figure is presented in groups of two elements (numbered at the bottom of each pair), representing a particular stimulus. Each histogram rectangle represents the psychophysical performance level with the element depicted below it in the foreground and the adjacent element in the background. Filled circles represent the prediction obtained by selecting the spatial frequency yielding the highest performance for each pair. The open circles represent predictions for Gabor filters having only larger wavelengths. Note that perfect correlation would place one class of circles on top of each histogram rectangle. (Vn = 0.05.)

Fig. 6
Fig. 6

Typical stimuli of psychophysical experiments: (a) has elements with random orientations, (b) has aligned elements, and (c) has elements with two orientations; (a)–(c) have dense spacing and (d) has sparsely spaced elements of two orientations.

Fig. 7
Fig. 7

Typical mask having elements comprising a +/┌ combination shown with randomly generated orientations.

Fig. 8
Fig. 8

Psychophysical results of three observers, AP, YG, and BR, for densely spaced stimuli having one orientation, two orientations, and random orientations. Asymmetry is marked by the spaces between the curves. Notice that asymmetry increases for textures having more orientations. The average standard error is depicted at the lower right-hand portion of the graph box.

Fig. 9
Fig. 9

Psychophysical results of three observers, SE, BR, and DS, for sparsely spaced stimuli having one orientation, two orientations, and random orientations. Notice that there exists great asymmetry for random orientation; however, there is little increase in asymmetry from one to two orientations.

Equations (13)

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G ev ( x , y | λ , θ , x c , y c ) = exp { [ ( x x c ) 2 + ( y y c ) 2 ] 2 σ 2 } × cos { ( 2 π / λ ) [ ( x x c ) cos θ ( y y c ) sin θ ] } ,
G od ( x , y | λ , θ , x c , y c ) = exp { [ ( x x c ) 2 + ( y y c ) 2 ] 2 σ 2 } × sin { ( 2 π / λ ) [ ( x x c ) cos θ ( y y c ) sin θ ] } ,
G L ev ( x c , y c | λ , θ ) = x , y G ev ( x , y | λ , θ , x c , y c ) · L ( x , y ) ,
G L od ( x c , y c | λ , θ ) = x , y G od ( x , y | λ , θ , x c , y c ) · L ( x , y ) ,
E ( x c , y c | λ , θ ) = G L ev 2 ( x c , y c | λ , θ ) + G L od 2 ( x c , y c | λ , θ ) .
T x , y ( λ , θ ) = x c , y c S ( x , y ) E ( x c , y c | λ , θ ) ,
P c = 0 p fb ( z ) [ 0 z p bb ( z ) d z ] 3 d z ,
T x , y ( λ , θ ) = x c , y c S ( x , y ) log [ E ( x c , y c | λ , θ ) + 1 ] ,
V bb = 2 V bn = 2 ( V b + V n ) ,
M fb = M fn M bn = M f M b ,
V fb = V fn + V bn = V f + V b + 2 V n .
p bb ( z ) = 2 2 π V bb exp ( z 2 2 V bb ) for z 0
p fb ( z ) = 1 2 π V fb { exp [ ( z M fb ) 2 2 V fb ] + exp [ ( z M fb ) 2 2 V fb ] } for z 0 ,

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