A binocular reconstruction method fused with Laplacian image information for pavement texture evaluation. (November 2021)

• Record Type: Journal Article
• Authors: Liu, Lu; Zhu, Pan; Guan, Jiaxi; Jiang, Rong; Zhou, Xinglin
• Is Part Of: Measurement. Volume 185(2021)
• Publication Date: 2021-11
• Subjects: Asphalt pavement -- Binocular reconstruction -- Cross-scale aggregation -- Areal texture parameters; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.110039
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Combine the captured pictures and their Laplacian images to improve the accuracy of pavement texture reconstruction. AD + gradient + Census transform as the matching cost reduces the mismatch of texture reconstruction. The areal texture parameter results of the proposed binocular method are close to those of the laser scanner. Abstract: 3D reconstruction technology based on image processing has the advantages of fast speed and high resolution to reconstruct pavement texture morphology for detecting the skid resistance. However, the small color difference and unobvious feature points of asphalt pavement lead to low accuracy in texture morphology reconstruction. A binocular technology fused with Laplacian image information was proposed to improve the precision of texture reconstruction as follow: the first mode without region segmentation, the second mode with laser region segmentation and the third mode with the region segmentation used template. The results show that the proposed algorithm improves the binocular reconstruction accuracy of pavement texture compared with the traditional SGBM algorithm. The proposed method and the laser scanner are compared through areal texture parameters. The results of the proposed method are relatively close to those of laser scanners.