Detecting Perceptually Parallel Curves: Criteria and Force-Driven Optimization

We have developed several theorems for the detection of parallel curves in the continuous space. In this paper, we studied issues in carrying the continuous algorithm to the discrete case and also the perceptual characteristics leading to human recognition of parallelism. By formulating these properties in terms of several distinctive forces, we developed a force-driven model as a new optimization strategy to perform correspondence establishment between points in the matching curves. This force-driven mechanism provides a good coupling (or correspondence matching) result, which is the prerequisite for the correct detection of parallelism between curves. Convergence of the algorithm and implementation efficiency are also investigated and discussed. Experimental results on the relative weightings of these forces also shed light on the perceptual priority imposed by the human vision system.

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