Evaluation of asphalt pavement texture using multiview stereo reconstruction based on deep learning

Dan, Han-Cheng; Lu, Bingjie; Li, Mengyu

doi:10.1016/j.conbuildmat.2023.134837

Cited by 12 publications

(1 citation statement)

References 41 publications

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“…Using filtered 3D data to generate a 3D virtual model of pavement texture, Liang et al [18] proposed a reference area integral method to evaluate pavement MTD. Dan et al [19] proposed a multi-view stereo reconstruction method based on deep learning to calculate the texture depth of asphalt pavement, so as to accurately evaluate the skidding resistance of asphalt pavement.…”

Section: Introductionmentioning

confidence: 99%

Research on the Skidding Resistance and Attenuation Characteristics of Asphalt Pavement Based on Image Recognition-Analysis Strategy

Zhang,

Xi,

Zhao

et al. 2024

Coatings

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To accurately evaluate the skidding resistance of asphalt pavements, a texture imaging device was developed to realize the standardized acquisition of pavement images. Based on the gray-level co-occurrence matrix and multifractal theory of texture structure, the influence of segregation degree and gradation type on the texture properties of asphalt pavement was studied. Meanwhile, a comprehensive evaluation index of skidding resistance was proposed for asphalt pavement. Furthermore, the attenuation characteristics of the anti-skidding performance for asphalt mixture were explored, and the corresponding attenuation model of asphalt pavement was established. The results show that the segregation degree and gradation type significantly affected the texture parameters and anti-skidding performance of asphalt mixture. Specially, with an increase in the segregation degree of coarse aggregate, the parameters of energy, entropy, and multifractal spectrum width gradually increased, whereas the inertial moment gradually decreased. The variation range of the multifractal spectrum difference initially increased and subsequently decreased. For the texture parameters such as energy, entropy, inertial moment, and multifractal spectrum width Δα, the values of the asphalt mixture with larger nominal maximum particle were higher than those of the mixture with smaller nominal maximum particle, whereas the multifractal spectrum difference value showed the opposite law. In addition, the texture parameters of energy, entropy, and multifractal spectrum width exhibited good linear correlation with the texture depth (TD) of asphalt mixtures with various segregation levels and gradation types. The index based on the texture parameters of energy, entropy, and multifractal spectrum width effectively evaluated the skidding resistance of asphalt pavements, which showed the same trend as the TD with the increase of the abrasion number. The achievement provides an effective solution for the evaluation of skidding resistance and attenuation characteristics of asphalt mixtures.

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Section: Introductionmentioning

confidence: 99%