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A Novel Decision Mechanism for Image Edge Detection

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Intelligent Computing Theories and Application (ICIC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12836))

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Abstract

Edge detection plays an important role in image processing and computer vision tasks such as image matching and image segmentation. In this paper, we argue that edges in image should always be detected even under different image rotation transformations or noise conditions. Then a novel edge detection method is presented for improving the robustness of image edge detection. Firstly, we perform the following operations on the input image to obtain a set of images: random destruction operation, random rotation operation, and randomly addition of Gaussian noise with zero mean and random variance. Secondly, multi-directional Gabor filters with multiple scales are used as a tool to smooth the set of images and obtain candidate edges from the set of images. Thirdly, a novel edge decision mechanism is designed with a 0.95 confidence interval for selecting true edges from the candidate edges. Finally, two edge detection evaluation criteria (i.e., the aggregate test receiver-operating-characteristic and the Pratt’s figure of merit) are utilized to evaluate the proposed edge detection method against five state-of-the-art methods. The experimental results show that our proposed method outperforms all the other tested methods.

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Acknowledgments

This work was supported by the Shaanxi Innovation Ability Support Program (2021TD-29)- Textile Intelligent Equipment Information and Control Innovation Team and Shaanxi innovation team of universities –Textile Intelligent Equipment Information and Control Innovation Team.

Author information

Authors and Affiliations

  1. School of Electrical and Information, Xi’an Polytechnic University, Xi’an, 710048, China

    Junfeng Jing, Shenjuan Liu, Chao Liu, Tian Gao & Weichuan Zhang

  2. CSIRO Data61, PO Box 76, Epping, NSW, 1710, Australia

    Weichuan Zhang & Changming Sun

Authors
  1. Junfeng Jing
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  2. Shenjuan Liu
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  3. Chao Liu
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  4. Tian Gao
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  5. Weichuan Zhang
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  6. Changming Sun
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Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Shenzhen University, Shenzhen, China

    Jianqiang Li

  4. Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

    Valeriya Gribova

  5. Polytechnic University of Bari, Bari, Italy

    Vitoantonio Bevilacqua

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Jing, J., Liu, S., Liu, C., Gao, T., Zhang, W., Sun, C. (2021). A Novel Decision Mechanism for Image Edge Detection. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Bevilacqua, V. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12836. Springer, Cham. https://doi.org/10.1007/978-3-030-84522-3_22

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  • DOI: https://doi.org/10.1007/978-3-030-84522-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84521-6

  • Online ISBN: 978-3-030-84522-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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