An object recognition system using stochastic knowledge source and VLSI parallel architecture

W. D. Mao, Sun-Yuan Kung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The authors present a system for 2-D shape recognition using hidden Markov model (HMM) knowledge sources. The shape is represented by a sequence of curvature values. A ring hidden Markov model (RHMM), which incorporates a ring structure and local connectivity, is proposed. The approach solves both the context sensitivity problem and the pattern instantiation problem. Simulation results on aircraft indicate that the proposed system can achieve almost 100% recognition accuracy at a very fast learning speed. It is shown that the RHMM system can be efficiently implemented in a systolic array, permitting real-time processing.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherPubl by IEEE
Pages832-836
Number of pages5
ISBN (Print)0818620625
StatePublished - Dec 1 1990
EventProceedings of the 10th International Conference on Pattern Recognition - Atlantic City, NJ, USA
Duration: Jun 16 1990Jun 21 1990

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1

Other

OtherProceedings of the 10th International Conference on Pattern Recognition
CityAtlantic City, NJ, USA
Period6/16/906/21/90

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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