Pattern recognition system

Image analysis – Histogram processing – For setting a threshold

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

382 15, 382 48, G06K 900

Patent

active

051425904

ABSTRACT:
A self-categorizing pattern recognition system includes an adaptive filter for selecting a category in response to an input pattern. A template is then generated in response to the selected category and a coincident pattern indicating the intersection between the expected pattern and the input pattern is generated. The ratio between the number of elements and the coincident pattern to the number of elements in the input pattern determines whether the category is reset. If the category is not reset, the adaptive filter and template may be modified in response to the coincident pattern. Reset of the selected category is inhibited if no expected pattern is generated. Weighting of the adaptive filter in response to a coincident pattern is inversely related to the number of elements in the input pattern. The selected categories reset where a reset function is less than a vigilance parameter which may be varied in response to teaching events.

REFERENCES:
patent: 3111646 (1963-11-01), Harmon
patent: 3191149 (1965-06-01), Andrews
patent: 3832683 (1974-08-01), Nadler et al.
patent: 3950733 (1976-04-01), Cooper et al.
patent: 4044243 (1977-08-01), Cooper et al.
patent: 4177448 (1979-12-01), Brayton
patent: 4254474 (1981-03-01), Cooper et al.
patent: 4319331 (1982-03-01), Elbaum et al.
patent: 4326259 (1982-04-01), Cooper et al.
patent: 4451929 (1984-05-01), Yoshida
patent: 4606069 (1986-08-01), Johnsen
patent: 4773099 (1988-09-01), Brokser
patent: 4805225 (1989-02-01), Clark
Carpenter, G. A. and Grossberg, S., "Category learning and adaptive pattern recognition: A neural network mode," Proceedings of the Third Army Conference on Applied Mathematics and Computing, 1986, ARO Report 86-1, pp. 37-56.
Carpenter, G. A. and Grossberg, S., "Neural dynamics of category learning and recognition: Attention, memory consolidation, and amnesia", In J. Davis, R. Newburgh and E. Wegman (Eds.), Brain Structure, Learning, and Memory, AAAS Symposium Series, 1987.
Carpenter, G. A. and Grossberg, S., "Neural dynamics of category learning and recognition: Structural invariants, reinforcement, and evoked potentials", In M. L. Commons, S. M. Kosslyn, and R. J. Herrnstein (Eds.), Pattern Recognition and Concepts in Animals, People, and Machines, Hillsdale, NJ: Erlbaum, 1987.
Carpenter, G. A. and Grossberg, S., "Adaptive resonance theory: Stable self-organization of neural recognition codes in response to arbitrary lists of input patterns", Proceedings Cognitive Science Society, 1986.
Carpenter, G. A. and Grossberg, S., "A massively parallel architecture for a self-organizing neural pattern recognition machine", Computer Vision, Graphics, and Image Processing, 1987.
Carpenter, G. A. and Grossberg, S., "Associative learning, adaptive pattern recognition, and competitive decision making by neural networks," Hybrid and Optical Computing, H. Szu, Ed. SPIE, 1986.
Aleksander I., et al., "Microcircuit learning nets: improved recognition by means of pattern feedback", Electronic Letters, GB, Oct. 1968, vol. 4, No. 20, pp. 425-426.
Irakhnenko, A. G., "Self-organizing systems with positive feedback loops" IEEE Trans. on Aut. Control, vol. AC-8, No. 3, Jul. 1963, pp. 247-254.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Pattern recognition system does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Pattern recognition system, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Pattern recognition system will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-391457

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.