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A parallel thinning algorithm based on stroke continuity detection

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Abstract

Thinning algorithms often cause stroke distortions at the crosses or intersections of strokes, which lead to bad results in pattern recognition tasks. In order to overcome these drawbacks, this paper proposes a parallel thinning algorithm based on stroke continuity detection. In the algorithm, before it uses the conditions of parallel algorithms to delete a boundary point, it first detects whether the boundary point is a reserved point to keep stroke’s continuity or not. Consequently, it can produce a skeleton with good symmetry, control the large deformation at the cross or intersection of strokes, and make a better skeleton more quickly. Moreover, it is practically immune to noise.

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Acknowledgements

This paper is supported by National Natural Science Foundation of China (Nos. 11501584, 61471132, 61372173), Guangzhou Key Lab of Body Data Science (No. 201605030011), Guangdong Province Data Science and Engineering Research Center’s Open Fund Project (No. 2016KF02), Guangdong province Medical science and technology research fund project (No. A2016147), and the Training program for outstanding young teachers in higher education institutions of Guangdong Province (No. YQ2015057).

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Authors and Affiliations

  1. School of Basic Courses, Guangdong Pharmaceutical University, Guangzhou, 510006, People’s Republic of China

    Jianwei Dong

  2. School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, People’s Republic of China

    Yanmei Chen

  3. School of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, People’s Republic of China

    Zhijing Yang & Bingo Wing-Kuen Ling

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  1. Jianwei Dong
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  2. Yanmei Chen
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  3. Zhijing Yang
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  4. Bingo Wing-Kuen Ling
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Correspondence to Bingo Wing-Kuen Ling.

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Dong, J., Chen, Y., Yang, Z. et al. A parallel thinning algorithm based on stroke continuity detection. SIViP 11, 873–879 (2017). https://doi.org/10.1007/s11760-016-1034-y

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