Fast computation of optimal polygonal approximations of digital planar closed curves.

Graphical Models(2016)

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摘要
A novel method to solve the min-# polygonal approximation problem is proposed.The approach uses a modified Mixed Integer Programming model to solve the min-# problem.The proposed model is smaller than previous proposals.The novel procedure obtains the optimal solution faster than state-of-the-art methods.Only one execution of our procedure is needed to assure the optimality of the solution. Display Omitted We face the problem of obtaining the optimal polygonal approximation of a digital planar curve. Given an ordered set of points on the Euclidean plane, an efficient method to obtain a polygonal approximation with the minimum number of segments, such that, the distortion error does not excess a threshold, is proposed. We present a novel algorithm to determine the optimal solution for the min-# polygonal approximation problem using the sum of square deviations criterion on closed curves.Our proposal, which is based on Mixed Integer Programming, has been tested using a set of contours of real images, obtaining significant differences in the computation time needed in comparison to the state-of-the-art methods.
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关键词
Digital planar curves,Polygonal approximation,Integral Square Error,Mixed Integer Programming,Discrete optimization,min-# polygonal approximation problem
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