Abstract
Point pattern matching (PPM) is a widely studied problem in algorithm research and has numerous applications, e.g., in computer vision. In this paper we focus on a class of brute force PPM algorithms suitable for situations where the state-of-the-art methods do not perform optimally, e.g., due to point sets with regular structure. We discuss of an existing algorithm, which is optimal in the sense of brute force testing of different point pairings. We propose a parameter choosing scheme that minimizes the memory consumption of the algorithm. We also present a modified version of the algorithm to overcome issues related to its implementation and accuracy. Due to its brute force nature, the algorithm is guaranteed to return the best possible result.
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Manninen, T., Rönkkä, R., Huttunen, H. (2011). Point Pattern Matching for 2-D Point Sets with Regular Structure. In: Heyden, A., Kahl, F. (eds) Image Analysis. SCIA 2011. Lecture Notes in Computer Science, vol 6688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21227-7_15
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DOI: https://doi.org/10.1007/978-3-642-21227-7_15
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