Abstract
We propose a neural network model for the figure-ground organization based on spatial arrangement of contours such as parallelism, symmetry, and on contour convexity. All of them have been manifested as effective factors for figure-ground organization by psychological studies. In order to measure parallelism and symmetry, spatially separated distant contours have to be corresponded. Our model process them by local detectors embedded in hierarchical architecture of network in which image data is pyramidally encoded. We tested our model by computer simulation and succeeded to mimic some human perceptions.
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References
Driver, J., Baylis, G.C.: Edge-assignment and figure-ground segmentation in short-term visual matching. Cognitive Psychology 31, 248–306 (1996)
Grossberg, S., Mingolla, E.: Neural dynamics of perceptual grouping: Texture, boundaries, and emergent segmentations. Perception & Psychophysics 38(2), 141–171 (1985)
Kanizsa, G., Gerbino, W.: Convexity and symmetry in figure-ground organization. In: Henle, M. (ed.) Vision and Artifact, pp. 25–32. Springer, New York (1976)
Kapadia, M.K., Ito, M., Gilbert, C.D., Westheimer, G.: Improvement in visual sensitivity by changes in local context: parallel studies in human observers and in V1 of alert monkeys. Neuron 15, 843–856 (1995)
Kikuchi, M., Akashi, Y.: A model of border-ownership coding in early vision. In: Dorffner, G., Bischof, H., Hornik, K. (eds.) ICANN 2001. LNCS, vol. 2130, pp. 1069–1074. Springer, Heidelberg (2001)
Kikuchi, M., Fukushima, K.: Neural network model of the visual system: binding form and motion. Neural Networks 9, 1417–1427 (1996)
Koffka, K.: Principles of Gestalt psychology. Routledge & Kegan Paul Ltd., London (1935)
Metzger, W.: Gesetze des Sehens. Verlag von Waldemar Kramer, Frankfurt am Main (1953)
Nakayama, K., He, Z.J., Shimojyo, S.: Visual surface representation: a critical link between low-level and higher level vision. In: Kosslyn, S.M., Osherson, D.N. (eds.) Visual Cognition, pp. 1–70. MIT Press, Cambridge (1995)
Fukushima, K.: Neocognitron: a hierarchical neural network model capable of visual pattern recognition. Neural Networks 1(2), 119–130 (1988)
Paupathy, A., Conner, E.: Responses to contour features in macaque area V4. Journal of Neurophysiology 82, 2490–2502 (1999)
Rubin, E.: Visuall wahrgenommene figuren. Copenhagen (1921)
Sajda, P., Finkel, L.H.: Intermediate-level visual representations and the construction of surface perception. Journal of Cognitive Neuroscience 7, 267–291 (1995)
Zhou, H., Friedman, H.S., von der Heydt, R.: Coding of border ownership in monkey visual cortex. The Journal of Neuroscience 20, 6594–6611 (2000)
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Kikuchi, M., Fukushima, K. (2003). Assignment of Figural Side to Contours Based on Symmetry, Parallelism, and Convexity. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_18
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DOI: https://doi.org/10.1007/978-3-540-45226-3_18
Publisher Name: Springer, Berlin, Heidelberg
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