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<p>Describes a method of recognizing objects whose contours can be represented in smoothly varying polar coordinate form. Both low- and high-level information about the object (contour smoothness and edge sharpness at the low level and contour shape at the high level) are incorporated into a single energy function that defines a 1D, cyclic, Markov random field (1DCMRF). This 1DCMRF is based on a polar coordinate object representation whose center can be initialized at any location within the object. The recognition process is based on energy function minimization, which is implemented by simulated annealing.</p>
1D cyclic Markov random field; pattern recognition; energy-function-based optimization; polar coordinate; contour smoothness; edge sharpness; simulated annealing; Markov processes; pattern recognition; simulated annealing
N.S. Friedland, A. Rosenfeld, "Compact Object Recognition Using Energy-Function-Based Optimization", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 770-777, July 1992, doi:10.1109/34.142912
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