Heuristic strategy for feature matching in parallel curve detection

Feature matching has been proved very efficient as an approach for curve matching. However, when there are lots of features detected in the two curves, the possible combinations of matching among these features are prohibitive computationally. In this paper, we propose a heuristic algorithm to select the most promising coupling schemes out of these possible patterns. For parallel curve detection, the rationales we employed include proximity measure and compatibility between tangent orientations at these feature points.