A cost minimization approach to edge detection using simulated annealing

Edge detection is analyzed as a problem in cost minimization. A cost function is formulated that evaluates the quality of edge configurations. A mathematical description of edges is given, and the cost function is analyzed in terms of the characteristics of the edges in minimum-cost configurations. The cost function is minimized by the simulated annealing method. A novel set of strategies for generating candidate states and a suitable temperature schedule are presented. Sequential and parallel versions of the annealing algorithm are implemented and compared. Experimental results are presented.<<ETX>>

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