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An improved industrial sub-pixel edge detection algorithm based on coarse and precise location

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Abstract

In this paper, an improved sub-pixel edge detection algorithm combining coarse and precise location is proposed. The algorithm fully considers the 8-neighborhood pixel information and keeps the Roberts operator’s advantages of high location accuracy and fast speed. Meanwhile, it can effectively suppress noise and obtain better detection results. In order to solve the problem of low efficiency of the Zernike moment method in threshold selection, the Otsu’s method is introduced to achieve accurate sub-pixel edge location. The experimental results show that the proposed algorithm effectively improves the detection efficiency and the detection accuracy.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China, under Grant Nos. 61762037, 61872141, 61462028, Natural Science Foundation of Jiangxi Province, under Grant No. 20181BAB206037, Excellent Scientific and Technological Innovation Teams of Jiangxi Province, under Grant No. 20181BCB24009 and Nanchang City Knowledge Innovation Team, under Grant No. 2016T75.

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Authors and Affiliations

  1. School of Information Engineering, East China Jiaotong University, Nanchang, People’s Republic of China

    Xin Xie, Songlin Ge & Nan Jiang

  2. School of Information Science Technology, East China Normal University, Shanghai, People’s Republic of China

    Mingye Xie

  3. School of Civil Engineering, East China Jiaotong University, Nanchang, People’s Republic of China

    Fengping Hu

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  1. Xin Xie
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  2. Songlin Ge
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  3. Mingye Xie
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  4. Fengping Hu
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  5. Nan Jiang
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Correspondence to Xin Xie.

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Xie, X., Ge, S., Xie, M. et al. An improved industrial sub-pixel edge detection algorithm based on coarse and precise location. J Ambient Intell Human Comput 11, 2061–2070 (2020). https://doi.org/10.1007/s12652-019-01232-2

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