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Asian Conference on Computer Vision

ACCV 2018: Computer Vision – ACCV 2018 pp 551–564Cite as

A Novel Multi-scale Invariant Descriptor Based on Contour and Texture for Shape Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11364))

Abstract

This paper proposes a novel multi-scale descriptor for shape recognition. The contour of shape is represented by a sequence of sample points with uniform spacing. Straight lines connected between two moving contour points are used to cut the shape. The lengths of the contour segments between the two sampled contour points determine the levels of scales. Then the geometric features of the cut contour and the interior texture features around the straight lines are extracted at each scale. This method not only has the powerful discriminability to describe a shape from coarse to fine, but also is invariant to scale, rotation, translation and mirror transformations. Experiments conducted on five image datasets (COIL-20, Flavia, Swedish, Leaf100 and ETH-80) demonstrate that the proposed method significantly outperforms the state-of-the-art methods.

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Acknowledgement

This work is partially supported by National Key R&D Program of China (No. 2016YFD0101903), National Natural Science Foundation of China (No. 61702386, 61672398), Major Technical Innovation Program of Hubei Province (No. 2017AAA122), Key Natural Science Foundation of Hubei Province of China (No. 2017CFA012), the Fundamental Research Funds for the Central Universities (No. 185210006).

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Authors and Affiliations

  1. Wuhan University of Technology, Wuhan, China

    Jishan Guo, Yi Rong, Ying Liu & Shengwu Xiong

  2. School of Engineering, Griffith University, Brisbane, QLD, 4111, Australia

    Yongsheng Gao

Authors
  1. Jishan Guo
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  2. Yi Rong
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  3. Yongsheng Gao
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  4. Ying Liu
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  5. Shengwu Xiong
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Corresponding author

Correspondence to Shengwu Xiong .

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Editors and Affiliations

  1. IIIT Hyderabad, Hyderabad, India

    C.V. Jawahar

  2. ANU, Canberra, ACT, Australia

    Hongdong Li

  3. Simon Fraser University, Burnaby, BC, Canada

    Greg Mori

  4. ETH Zurich, Zurich, Zürich, Switzerland

    Konrad Schindler

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Guo, J., Rong, Y., Gao, Y., Liu, Y., Xiong, S. (2019). A Novel Multi-scale Invariant Descriptor Based on Contour and Texture for Shape Recognition. In: Jawahar, C., Li, H., Mori, G., Schindler, K. (eds) Computer Vision – ACCV 2018. ACCV 2018. Lecture Notes in Computer Science(), vol 11364. Springer, Cham. https://doi.org/10.1007/978-3-030-20870-7_34

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  • DOI: https://doi.org/10.1007/978-3-030-20870-7_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20869-1

  • Online ISBN: 978-3-030-20870-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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