Abstract
Artificial Intelligence (AI) deals with the types of problem solving and decision making that humans continuously face in dealing with the world. Such activity involves by its very nature complexity, uncertainty, and ambiguity which can “distort” the phenomena (e.g., imagery) under observation. However, following the human example, any artificial vision system should process information such that the results are invariant to the vagaries of the data acquisition process.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ballard, D.H., C.M. Brown (1982), “Computer Vision,” Prentice Hall, 1982.
Ballard, D.H., G.E. Hinton, T.J. Sejnowski, (1983), Parallel visual computation, “Nature,” 306, 5938, 21–26.
Barrow, H.G., J.M. Tenenbaum (1978), Recovering intrinsic scene characteristics from images, in “Computer Vision Systems,” A. Hanson and E. Riseman (Eds.), Academic Press.
Brooks, R. (1981), Symbolic reasoning among 3-D models and 2-D images, “Artificial Intelligence,” 17, 1–3.
Caulfield, H.J., M.H. Weinberg (1982), Computer recognition of 2-D pattern using generalized matched filters, “Applied Optics,” 21,9.
Davis, L.S., A. Rosenfeld, (1981), Cooperating processes for low-level vision: a survey, “Artificial Intelligence,” 17, 1–3, 245–263.
Edelman, G.M. (1982), Group selection and higher brain function, “Bulletin of the American Academy of Arts and Science,” vol. XXXVI, 1.
Farah, M.J. (1985), The neurological basis of mental imagery: a componential analysis, in “Visual Cognition,” S. Pinker (Ed.), MIT Press.
F la veil, J.H. (1985), “Cognitive Development,” (2nd Ed.), Prentice Hall.
Fukushima, K. (1984), A hierarchical neural network model for associative memory, “Biol. Cybernetics,” 50, 105–113.
Garvey, T.D., J.D. Lowrance (1983), Evidential reasoning: an implementation for multisensor integration, TN307, AI Center, SRI, Palo Alto, CA.
Granrud, C., R. Haake, A. Yonas (1985), Sensitivity to familiar size: the effects of memory on spatial perception, “Perception Psychophysics,” 37, 459–466.
Hester, C., Casasent, D. (1981), Interclass discrimination using synthetic discriminant functions (SDF), “Proc. SPIE on Infrared Technology for Target Detection and Classification,” Vol. 302.
Hopfield, J.J. (1982), Neural networks and physical systems with emergent collective computational abilities, “Proc. Natl. Acad. Sci. USA,” 79, April 1982.
Hubel, D., Wiesel, T., (1979), Brain mechanisms of vision, “Scientific American “October.
Jacobson, L., H. Wechsler (1985a), Joint spatial/spatial frequency representations for image processing, “SPIE/Cambridge Int. Conference on Intelligent Robots and Computer Vision,” Boston, MA.
Jacobson, L., H. Wechsler (1985b), FOVEA — A system for invariant visual form recognition, “2nd Int. Symposium on Optical and Electro-Optical Applied Science and Recognition,” Cannes, France.
Kirpatrick, S., C.D. Gelatt, M.P. Vecchi (1983), Optimization by simulated annealing, “Science,” 220, 671.
Kohonen, T. (1984), “Self-Organization and Associative-Memories,” Springer-Verlag.
Kuhn, T. (1970), “The Structure of Scientific Revolution,” The University of Chicago Press.
Minsky, M., S. Papert (1968), “Perceptrons,” MIT Press.
Mulgaonkar, P.G., L.G. Shapiro (1985), Hypothesis-based geometric reasoning about perspective images, “Proc. of the Third Workshop on Computer Vision, Representation and Control” Bellaire, Michigan.
Nahar, S., S. Sahni, E. Shragowitz (1985), Simulated annealing and combinatorial optimization, TR 85–56, Dept. of Computer Science, University of Minnesota.
Searl, J. (1985), “Mind, Brain and Science,” Harvard University Press.
Simon, H.A., (1984), “The Science of the Artificial,” (2nd ed.), MIT Press.
Tanimoto, S., T. Pavlidis (1975), A hierarchical data structure for picture processing, “Computer Graphics and Image Processing,” 4, 2, 104–119.
Van Essen, D.C., J.H.R. Marniseli (1983), Hierarchical organization and functional streams in the visual cortex, TINS (Trends in Neuro Sciences).
Witkin, A.P., J.M. Tenenbaum (1983), On the role of structure in vision, in “Human and Machine Vision,” J. Beck, B. Hope and A. Rosenfeld (Eds.), Academic Press.
Wittgenstein, L. (1953), “Philosophical Investigations,” MacMillan.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1987 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wechsler, H. (1987). Network Representations and Match Filters for Invariant Object Recognition. In: Devijver, P.A., Kittler, J. (eds) Pattern Recognition Theory and Applications. NATO ASI Series, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83069-3_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-83069-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-83071-6
Online ISBN: 978-3-642-83069-3
eBook Packages: Springer Book Archive