Semiconductor Optoelectronics, Volume. 45, Issue 3, 508(2024)

Pavement Crack Feature Extraction Based on Image Processing

DAI Shaosheng1... MAO Xinghua1 and YU Zian2 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    References(8)

    [2] [2] KheradmandiN,Mehranfar V.A critical review and comparative study on image segmentation-based techniquesfor pavement crack detection[J] .Constr.Build.Mater.,2022,321: 126162.

    [4] [4] Vivekananthan V,Vignesh R,Vasanthaseelan S,et al.Concrete bridge crack detection by image processing technique by using the improved OTSU method [J] .Mater.Today Proc.,2023,74(4) : 1002-1007.

    [5] [5] Pham M V,Ha Y S,Kim Y T.Automatic detection and measurementofground crack propagation using deep learning networks and an image processing technique [J] .Measurement,2023,215: 112832.

    [7] [7] LiZ,Yin C,Zhang X.Crack segmentation extraction and parameter calculation of asphalt pavement based on image processing[J] .Sensors,2023,23(22) : 9161.

    [8] [8] DengJ,Lu Y,Lee V C S.A hybrid lightweight encoder- decoder network for automatic bridge crack assessment with real-world interference [ J ] .Measurement,2023,216: 112892.

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    [11] [11] TangY,Huang Z,Chen Z,et al.Novel visual crack width measurement based on backbone double-scale features for improved detection automation[J] .Eng.Struct.,2023,274: 115158.

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    DAI Shaosheng, MAO Xinghua, YU Zian. Pavement Crack Feature Extraction Based on Image Processing[J]. Semiconductor Optoelectronics, 2024, 45(3): 508

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    Paper Information

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    Received: Jan. 3, 2024

    Accepted: --

    Published Online: Oct. 15, 2024

    The Author Email:

    DOI:10.16818/j.issn1001-5868.2024010304

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