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A Pavement Crack Detection Method Combining 2D with 3D Information Based on Dempster‐Shafer Theory
Author(s) -
Huang Jianping,
Liu Wanyu,
Sun Xiaoming
Publication year - 2014
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12041
Subject(s) - dempster–shafer theory , laser scanning , road surface , grayscale , computer science , artificial intelligence , computer vision , scale (ratio) , image (mathematics) , cracking , gray (unit) , laser , materials science , optics , geography , medicine , physics , cartography , composite material , radiology
Pavement cracking is one of the main distresses presented in the road surface. Objective and accurate detection or evaluation for these cracks is an important task in the pavement maintenance and management. In this work, a new pavement crack detection method is proposed by combining two‐dimensional (2D) gray‐scale images and three‐dimensional (3D) laser scanning data based on Dempster‐Shafer (D‐S) theory. In this proposed method, 2D gray‐scale image and 3D laser scanning data are modeled as a mass function in evidence theory, and 2D and 3D detection results for pavement cracks are fused at decision‐making level. The experimental results show that the proposed method takes advantage of the respective merits of 2D images and 3D laser scanning data and therefore improves the pavement crack detection accuracy and reduces recognition error rate compared to 2D image intensity‐based methods.