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

The authors present a system for 2D 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