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Selecting and optimizing distress feature descriptors from multi-source images for pavement distress classification

Aidi Wang Hong Lang Yichuan Peng Xinting Chen Jinsong Qian

International Journal of Transportation Science and Technology2026，Vol.22Issue(2)：P.383-409,27.

International Journal of Transportation Science and Technology2026，Vol.22Issue(2)：P.383-409,27.DOI:10.1016/j.ijtst.2025.05.003

Selecting and optimizing distress feature descriptors from multi-source images for pavement distress classification

Aidi Wang ¹Hong Lang ²Yichuan Peng ¹Xinting Chen ¹Jinsong Qian¹

作者信息

1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China
2. Department of Civil and Environmental Engineering,University of Illinois Urbana-Champaign,Urbana,IL 61801,United States
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摘要

关键词

Pavement distress detection/Feature descriptors selection/Multi-source image texture analysis/Machine learning/Three-dimensional(3D)line laser technology

分类

交通工程

引用本文复制引用

Aidi Wang,Hong Lang,Yichuan Peng,Xinting Chen,Jinsong Qian..Selecting and optimizing distress feature descriptors from multi-source images for pavement distress classification[J].International Journal of Transportation Science and Technology,2026,22(2):P.383-409,27.

基金项目

supported by the National Natural Science Foundation of China(No.62206201) （No.62206201）

the Science and Technology Project of Henan Provincial Department of Transportation of China(No.2023-1-1) （No.2023-1-1）

the Key Research and Development Program of Yunnan Province of China(No.202303AA080016). （No.202303AA080016）

International Journal of Transportation Science and Technology

ISSN：2046-0430

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