Techniques including minimal path can efficiently extract curve-like structures by optimally finding the integral minimal-cost path between two seed points. In the first method, a novel minimal path-based algorithm which works on more general curve structures with fewer demands on the user for initial input compared to prior algorithms based on minimal paths. The main novelties and benefits of this new approach are that it may be used to find both closed and open curves, including complex topologies containing both multiple branch points and multiple closed cycles without demanding pre-knowledge about which of these types is to be extracted, and it requires only one input point which, in contrast to older methods, is no longer constrained to be an endpoint of the desired curve but truly may be any point along the desired curve. The second method MPP-BT (Minimal Path Propagation with Backtracking) first applies a minimal path propagation from one single starting point and then, at each reached point,backtracks few steps back to the starting point. Researchers in different areas like geometric optics, computer vision, robotics, and wire routing have previously solved related minimum-cost path problems using graph search and dynamic programming principles.

Curve Detection; Minimal Path Propagation with Unknown end points; key points; accumulation problem; backtracking; stop propagation

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