Abstract

This paper discusses the problem of introducing feedback in multilevel machine-vision systems. Based on a theoretical-informational analysis, it is shown that feedback is needed in such systems because the individual components of the quality criterion common to the entire system are optimized at different levels. As a result, the decisions made at the earlier stages of the analysis use only part of the components of this criterion, and this makes these decisions less than optimal. An approach is proposed to introduce feedback as a method of achieving the global optimum of the informational quality criterion by iterative improvement of the decision. Based on these results, it is shown that the information contained in the contours is inadequate for a robust construction of the structural elements.

© 2007 Optical Society of America

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  1. A. Rares, M. J. T. Reinders, and E. A. Hendriks, "Image Interpretation Systems," Technical Report (MCCWS 2.1.1.3.C), TU Delft, 1999.
  2. A. Gove, S. Grossberg, and E. Mingolla, "Brightness perception, illusory contours, and corticogeniculate feedback," Visual Neurosci. 12, 1027 (1995).
  3. C.-E. Liedtke, O. Grau, and S. Growe, "Use of explicit knowledge for the reconstruction of 3-D object geometry," in International Conference on Computer Analysis of Images and Patterns, 1995, pp. 580-587.
  4. R. M. Kozlov, Adaptation and Training in Robotics (Nauka, Moscow, 1990).
  5. A. S. Potapov, Pattern Recognition and Machine Perception. General Approach Based on the Principle of Minimum Description Length (Politekhnika, St. Petersburg, 2007).
  6. S. Grossberg, "Adaptive pattern classification and universal recoding. I: Parallel development and coding of neural feature detectors," Biol. Cybern. 23, 121 (1976) S. Grossberg, and "II: Feedback, expectation, olfaction, and illusions," Biol. Cybern. 23, 187 (1976).
  7. S. Grossberg, "Adaptive resonance theory," Technical Report CAS/CNS TR-2000-024, in The Encyclopedia of Cognitive Science (Macmillan, London, 2003).
  8. S. K. Kopparapu and U. B. Desai, "Bayesian Approach to Image Interpretation," Springer International Series in Engineering and Computer Science, 2001, vol. 616.
  9. M. Li and P. Vitanyi, "Philosophical Issues in Kolmogorov complexity," Proc. ICALP92 (invited lecture), 1992, pp. 1-15.

1995 (1)

A. Gove, S. Grossberg, and E. Mingolla, "Brightness perception, illusory contours, and corticogeniculate feedback," Visual Neurosci. 12, 1027 (1995).

Visual Neurosci. (1)

A. Gove, S. Grossberg, and E. Mingolla, "Brightness perception, illusory contours, and corticogeniculate feedback," Visual Neurosci. 12, 1027 (1995).

Other (8)

C.-E. Liedtke, O. Grau, and S. Growe, "Use of explicit knowledge for the reconstruction of 3-D object geometry," in International Conference on Computer Analysis of Images and Patterns, 1995, pp. 580-587.

R. M. Kozlov, Adaptation and Training in Robotics (Nauka, Moscow, 1990).

A. S. Potapov, Pattern Recognition and Machine Perception. General Approach Based on the Principle of Minimum Description Length (Politekhnika, St. Petersburg, 2007).

S. Grossberg, "Adaptive pattern classification and universal recoding. I: Parallel development and coding of neural feature detectors," Biol. Cybern. 23, 121 (1976) S. Grossberg, and "II: Feedback, expectation, olfaction, and illusions," Biol. Cybern. 23, 187 (1976).

S. Grossberg, "Adaptive resonance theory," Technical Report CAS/CNS TR-2000-024, in The Encyclopedia of Cognitive Science (Macmillan, London, 2003).

S. K. Kopparapu and U. B. Desai, "Bayesian Approach to Image Interpretation," Springer International Series in Engineering and Computer Science, 2001, vol. 616.

M. Li and P. Vitanyi, "Philosophical Issues in Kolmogorov complexity," Proc. ICALP92 (invited lecture), 1992, pp. 1-15.

A. Rares, M. J. T. Reinders, and E. A. Hendriks, "Image Interpretation Systems," Technical Report (MCCWS 2.1.1.3.C), TU Delft, 1999.

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