A recurrent neural architecture mimicking cortical preattentive vision systems

Neurocomputing

Volumn 11, Issue 2-4, 1996, Pages 155-170

  Indiveri, Giacomo ^a   Raffo, Luigi ^b   Sabatini, Silvio P ^a   Bisio, Giacomo M ^a  

^a UNIVERSITY OF GENOA   (Italy)

^b UNIVERSITY OF CAGLIARI   (Italy)

Author keywords

Recurrent architecture; Texture perception; Visual cortex model

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; COMPUTER VISION; FEATURE EXTRACTION; IMAGE PROCESSING;

PREATTENTIVE VISUAL TASKS; RECURRENT NEURAL ARCHITECTURE; TEXTURE PERCEPTION; VISUAL CORTEX;

NEURAL NETWORKS;

ANIMAL CELL; ARTICLE; ARTIFICIAL NEURAL NETWORK; CYTOARCHITECTURE; EVOKED VISUAL RESPONSE; NERVE CELL NETWORK; NONHUMAN; PRIORITY JOURNAL; RECEPTIVE FIELD; TACTILE DISCRIMINATION; TASK PERFORMANCE; VISUAL DISCRIMINATION; VISUAL SYSTEM;

EID: 0030175810     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/0925-2312(94)00067-0     Document Type: Article

References (45)

1. B. Julesz and Bergen, Textons, the fundamental elements in preattentive vision and perception, Bell System Tech. J. 62 (6) (1983).
2. C. Mead, Neuromorphic electronic systems, Proc. IEEE 78 (1990) 1629-1636.
3. C. Mead, Analog VLSI and Neural Systems (Addison-Wesley, Reading, 1989).
4. H. Kobayashi, J. White and A. Abidi, An active resistor network for Gaussian filtering of images, IEEE J. Solid State Circuits 26 (May 1991) 738-748.
5. L. Raffo, S. Sabatini, D. Caviglia and G. Bisio, Anisotropic active resistor meshes for implementing image processing operators, Electronics Letters 29 (May 1993) 960-961.
6. H. Barlow, Single units and sensation: A neuron doctrine for perceptual psychology? Perception 1 (1972) 371-394.
7. D. Hubel and T. Wiesel, Receptive fields and functional architecture in the two nonstriate visual areas (18 and 19) of the cat, J. Neurophysiol. 160 (1965) 106-154.
8. J. Kulikowski and T. Vidyasagar, Space and spatial frequency: Analysis and representation in the macaque striate cortex, Exp. Brain Res. 64 (1986) 5-18.
9. M. Hawken and A. Parker, Spatial receptive field organization in monkey V1 and its relationship to the cone mosaic, in Computational Models of Visual Processing (M. Landy and J. Movshon, eds.) (MIT Press, 1991) 83-93.
10. G. DeAngelis, I. Ohzawa and R. Freeman, Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex II. Linearity of temporal and spatial summation, J. Neurophysiol. 69 (1993) 1118-1135.
11. D. Heeger, Nonlinear model of neural responses in cat visual cortex, in Computational Models of Visual Processing (M. Landy and J. Movshon, eds.) (MIT Press, 1991) 119-133.
12. D. Albrecht and W. Geisler, Motion selectivity and the contrast-response function of simple cells in the visual cortex, Visual Neuroscience (1991) 531-546.
13. D. Ferster and B. Jagadeesh, Nonlinearity of spatial summation in simple cells of area 17 and 18 of cat visual cortex, J. Neurophysiol. 5 (1991) 1667-1679.
14. V. Glezer, V. Ivanov and T. Tscherbach, Investigation of complex and hypercomplex receptive fields of visual cortex of the cat as spatial frequency filters, Vision Res. 13 (1973) 1875-1904.
15. B. Skottun, R. De Valois, D. Grosof, J. Movshon, D. Albrecht and A. Bonds, Classifying simple and complex cells on the basis of response modulation, Vision Res. 31 (1991) 1079-1086.
16. R. Emerson, M. Korenberg and M. Citron, Identification of complex-cell intensive nonlinearities in a cascade model of cat visual cortex, Biol. Cybern. 66 (1992) 291-300.
17. D. Hubel and T. Wiesel, Receptive fields, binocular interaction and functional architecture in the cat's visual cortex, J. Physiol. 160 (1962) 106-154.
18. R. Emerson, M. Citron, W. Vaughn and S. Klein, Nonlinear directional sensitive subunits in complex cells of cat striate cortex, J. Neurophysiol. 58 (1987) 33-65.
19. S. Marlin, R. Douglas and M. Cynader, Position-specific adaptation in complex cell receptive fields of the cat striate cortex, J. Neurophysiol. 69 (1993) 2209-2221.
20. R. Szulborski and L. Palmer, The two-dimensional spatial structure of nonlinear subunits in the receptive fields of complex cells, Vision Res. 30 (1990) 249-254.
21. K. Albus, A quantitative study of the projection area of the central and the paracentral visual field in area 17 of the cat, Exp. Brain Res. 24 (1975) 159-202.
22. V. Braitenberg and C. Braitenberg, Geometry of orientation columns in the visual cortex, Biol. Cybern. 33 (1979) 179-176.
23. W. Baxter and B. Dow, Horizontal organization of orientation-sensitive cells in primate visual cortex, Biol. Cybern. 61 (1989) 171-182.
24. T. Bonhoeffer and A. Grinvald, The layout of iso-orientation domains in Area 18 of cat visual cortex: Optical imaging reveals a pinwheel-like organization, J. Neuroscience 13 (1993) 4157-4180.
25. J. Malik and P. Perona, Preattentive texture discrimination with early vision mechanisms, J. Opt. Soc. Amer. 1 (1990) 923-932.
26. D. Burr, M. Morrone and D. Spinelli, Evidence for edge and bar detectors in human vision, Vision Res. 29 (1989) 419-431.
27. J. Bergen and M. Landy, Computational modeling of visual texture segregation, in Computational Models of Visual Processing (M. Landy and J. Movshon, eds.) (MIT Press, 1991) 253-271.
28. D. Burr, M. Morrone and A. Fiorentini, Electro-physiological investigation of edge-selective mechanisms of human vision, Vision Res. 32 (1992) 239-247.
29. G. Bisio, D. Caviglia, G. Indiveri, L. Raffo and S. Sabatini, A neural network architectural model of visual cortical cells for texture segregation, in Proc. Int. Conf. on Neural Networks San Francisco, CA (March 1993).
30. P. Brodatz, Textures, a Photographic Album for Artists and Designers (New York, Dover, 1966).
31. J. Bolz and C. Gilbert, Generation of end-inhibition in the visual cortex via interlaminar connections, Nature, 320 (1986) 362-365.
32. R. von der Heydt and E. Peterhans, Cortical contour mechanisms and geometrical illusions, in Neural Mechanisms of Visual Perception (MIT press, 1989) 157-170.
33. R. von der Heydt and E. Peterhans, Mechanisms of contour perception in monkey visual cortex. I. Lines of pattern discontinuity, J. Neuroscience 9 (1989) 1731-1748.
34. A. Bonds, Dual inhibitory mechanisms for definition of receptive field characteristics in cat striate cortex, in Advances in Neural Information Processing Systems 3 (J.M.R.P. Lippmann and D. Touretzky, eds.) (Morgan Kaufmann, 1991) 75-82.
35. L. Bauman and A. Bonds, Inhibitory refinement of spatial frequency selectivity in single cells of the cat striate cortex, Vision Res. 31 (1991) 933-944.
36. F. Crick, Function of the thalamic reticular complex: The searchlight hypothesis, Proc. Natl. Acad. Sci. 81 (1984) 4586-4590.
37. A. Sillito, J. Cudeiro, and P. Murphy, Orientation sensitive elements in the corticofugal influence on centre-surround interactions in the dorsal lateral geniculate nucleus, Exp. Brain Res. 93 (1993) 6-16.
38. W. von Seelen, H. Mallot and F. Giannakopoulos, Characteristics of neuronal systems in the visual cortex, Biol. Cybern. 56 (1987) 37-49.
39. S. Grossberg, E. Mingolla and D. Todovoric, A neural network architecture for preattentive vision, IEEE Trans. Biomed. Eng. 36 (1989) 65-83.
40. D. Burr and M. Morrone, A nonlinear model of feature detection, in Nonlinear Vision: Determination of Neural Receptive Fields, Functions, and Networks (CRC press, 1992) 309-328.
41. B. Manjunath and R. Chellappa, A unified approach to boundary perception: Edges, textures and illusory contours, IEEE Trans. Neural Net. 4 (1993) 96-107.
42. L. Finkel and G. Edelman, Integration of distributed cortical systems by reentry: A computer simulation of interactive functionally segregated visual areas, J. Neuroscience 9 (1989) 3188-3208.
43. K. Fukushima, S. Miyake, and T. Ito, Neocognitron: A neural network model for a mechanism of visual pattern recognition, IEEE Trans. Syst. Man Cybern. 13 (5) (1983) 826-834.
44. K. Fukushima, Neural networks for visual pattern recognition, IEICE Trans. E74 (1) (1991) 179-190.
45. M. Turner, Texture discrimination by Gabor functions, Biol. Cybern. 55 (1986) 71-82.