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k-Attempt Thinning

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Combinatorial Image Analysis (IWCIA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12148))

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Abstract

Thinning is a frequently used approach to produce all kinds of skeleton-like shape features in a topology-preserving way. It is an iterative object reduction: some border points of binary objects are deleted, and the entire process is repeated until stability is reached. In the conventional implementation of thinning algorithms, we have to investigate the deletability of all border points in each iteration step. In this paper, we introduce the concept of k-attempt thinning (\(k\ge 1\)). In the case of a k-attempt algorithm, if a border point ‘survives’ at least k successive iterations, it is ‘immortal’ (i.e., it belongs to the produced feature). We propose a computationally efficient implementation scheme for k-attempt thinning. It is shown that an existing parallel thinning algorithm is 5-attempt, and the advantage of the new implementation scheme over the conventional one is also illustrated.

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Acknowledgments

This research was supported by the project “Integrated program for training new generation of scientists in the fields of computer science”, no EFOP-3.6.3-VEKOP-16-2017-00002. This research was supported by grant TUDFO/47138-1/2019-ITM of the Ministry for Innovation and Technology, Hungary.

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Correspondence to Kálmán Palágyi .

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Palágyi, K., Németh, G. (2020). k-Attempt Thinning. In: Lukić, T., Barneva, R., Brimkov, V., Čomić, L., Sladoje, N. (eds) Combinatorial Image Analysis. IWCIA 2020. Lecture Notes in Computer Science(), vol 12148. Springer, Cham. https://doi.org/10.1007/978-3-030-51002-2_19

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  • DOI: https://doi.org/10.1007/978-3-030-51002-2_19

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  • Online ISBN: 978-3-030-51002-2

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