The application of genetic algorithm in curve polygon approximation In the polygon approximation of planar digital curves, in order to overcome the vertex detection, it only depends on the local area and the weakness of global information The problem of shape approximation is optimized to find the minimum number of vertices and minimize the number of vertices and approximate errors under certain approximate error conditions In order to be able to deal with more points, genetic algorithm and improved genetic algorithm based on Pareto optimal solution are used to approximate the most The experimental comparison of some classical algorithms shows that the algorithm is more realistic and efficient than a class of algorithms that rely only on the local characteristics of the curve There are obvious improvements, and there are significant time savings for algorithms such as dynamic programming, such as dynamic programming.

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