Measurement of coarse aggregates movement characteristics within asphalt mixture using digital image processing methods

Shi, Liwan; Wang, Duanyi; Jin, Changning; Li, Ben; Liang, Hehao

doi:10.1016/j.measurement.2020.107948

Cited by 43 publications

(7 citation statements)

References 26 publications

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“…As the carrier of information collection, transmission, and storage, it plays an important role in daily production and life [3]. The technology related to digital image processing has been greatly developed, and two ways of application have gradually formed: one is to change the graphic information according to people's visual habits, so as to obtain high-quality visual interpretation, and tt can handle the process of image acquisition, transmission, and storage well [4,5].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Color Enhancement Processing for Plane Images Based on Computer Vision

Jiao

2022

Journal of Sensors

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As the main carrier of information transmission, plane images play an important role in the current network era. In order to enhance the color of the plane image, optimize the image effect, and solve the problem of image distortion with large color difference, a color enhancement processing optimization method is proposed based on the technical support of computer vision. According to computer vision theory, a computer vision model for adjusting perceived color and brightness is constructed. Combining it with the bilateral filtering algorithm, a color enhancement processing optimization model is obtained, which consists of three main stages: illumination information parameter estimation and image color correction, reflection coefficient parameter estimation and image color correction, and adaptive filtering. By estimating illumination information parameters and reflection coefficient parameters, the secondary gamma correction of image color is realized. After being processed by the bilateral filtering algorithm, the final optimized image is obtained. Verified by the subjective and objective evaluation results, the positive correlation index values of this method are all high, 8.0246, 16.4526, 0.9037, and 15.0246, respectively, and the negative correlation index value is low, 49.4169. It is proved that the proposed method can effectively suppress the halo and artifacts and obtain the image color quality that satisfies the visual perception. It not only enhances the image color but also retains the details to the greatest extent.

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Section: Introductionmentioning

confidence: 99%

Optimization of Color Enhancement Processing for Plane Images Based on Computer Vision

Jiao

2022

Journal of Sensors

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“…The closed holes were filled, the holes inside the aggregates were removed, and the image was dilated to restore the size of the aggregates. Finally, the watershed algorithm [ 17 , 18 , 30 ] was applied to separate further the adhered aggregates. The outcome of the treatment is shown in Figure 10 .…”

Section: Image-processing Methods For Asphalt Mixturementioning

confidence: 99%

“…Within research on asphalt-mixture CT image processing, the focus has mainly been placed on the methods emloyed to separate aggregate, mortar, and void within the image [ 14 , 15 ]. Currently, commonly used methods include the artificial threshold method [ 16 , 17 , 18 ], fuzzy C-means algorithm [ 19 , 20 ], Gaussian mixture model [ 21 ], and Otsu algorithm [ 22 , 23 , 24 , 25 ]. The most widely used is the Otsu algorithm.…”

Section: Introductionmentioning

confidence: 99%

Study on the Extraction of CT Images with Non-Uniform Illumination for the Microstructure of Asphalt Mixture

et al. 2022

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An adaptive image-processing method for CT images of asphalt mixture is proposed in this paper. Different methods are compared according to the error analysis calculated between the real gradation and 3D reconstruction gradation. As revealed by the test results, the adaptive image-processing method was effective in carrying out different brightness homogenization processes for each image. The Wiener filter with 7 × 7 size filter was able to produce a better noise reduction effect without compromising image sharpness. Among the three methods, the adaptive image-processing method performed best in the accuracy of coarse aggregate recognition, followed by the ring division method and the global threshold segmentation method. The error of the gradation extracted by the adaptive image-processing method was found to be lowest compared with the real gradation. For a variety of engineering applications, the developed method helps to improve the analysis of CT images of asphalt mixtures.

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“…Studies of asphalt skeletons mainly focus on the analysis of mixture stability based on the characterization of skeleton structures, in which two‐dimensional (2‐D) and three‐dimensional (3‐D) skeletons were investigated using micromechanical simulations in finite element (FE) and discrete element (DE) methods. Mixture stability herein refers to fatigue performance (Huang et al., 2020), creep performance (Ding et al., 2018), anti‐rutting performance (Ma et al., 2016), coarse aggregate movement (S. Li et al., 2020; Shi, Wang, Jin, et al., 2020) and other features. The skeleton structure is usually characterized as the morphology (Ding et al., 2017; P. Liu et al., 2017; Wang et al., 2020; Xiao & Tutumluer, 2016) and size range of constituent aggregates (Chen et al., 2015; Pouranian & Haddock, 2019; Ren & Yin, 2020; Y. Zhang et al., 2019), and the properties of force chains, including their shape (Bassett et al., 2015), length (Wang et al., 2020), contact condition (P. Li et al., 2020), bearing capacity (Y. Zhang et al., 2019), and quantity and distribution (Chang et al., 2020; G. Liu et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Stability prediction for asphalt mixture based on evolutional characterization of aggregate skeleton

Jin

Wan

Liu

et al. 2021

Computer aided Civil Eng

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The aggregate skeleton significantly influences the deformation resistance of asphalt mixtures. A stable skeleton has good interlocking effects and load transfer ability to resist deformation of mixtures during loading. Therefore, the methodology to accurately evaluate the morphology of aggregate skeleton based on the mechanism of load transfer inside mixtures is of great value to predict the mixture stability. The objective of this study is to predict and validate mixture stability from the perspective of evolutional morphologies of the skeleton.The methodology has three main steps, which are as follows: (1) the initial morphology of the aggregate skeleton is characterized and evaluated; (2) the topological and non-topological evolutions of the skeleton morphology during external loading are characterized; and (3) the strain energy of the mixture and the stress distribution on contact regions in the skeleton are used to analyze and validate the prediction of the mixture's stability. Simulations of uniaxial displacementcontrolled tests of three cylindrical specimens drilled in a field-compacted test track were conducted, and 7.5, 15, 22.5, and 30 s were selected as time points in the simulation to analyze mixture stability. Results indicate that a mixture has a better load-bearing capacity when its initial skeleton contains more chains with higher evaluation indices, which proves the reliability of the stability prediction using the proposed method.

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Measurement of coarse aggregates movement characteristics within asphalt mixture using digital image processing methods

Cited by 43 publications

References 26 publications

Optimization of Color Enhancement Processing for Plane Images Based on Computer Vision

Optimization of Color Enhancement Processing for Plane Images Based on Computer Vision

Study on the Extraction of CT Images with Non-Uniform Illumination for the Microstructure of Asphalt Mixture

Stability prediction for asphalt mixture based on evolutional characterization of aggregate skeleton

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