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Abstract
Pavement crack analysis, which deals with crack detection and crack growth detection, is a crucial task for modern Pavement Management Systems (PMS). This paper proposed a novel approach that uses historical crack data as reference for automatic pavement crack analysis. At first, a multi-scale localization method, which including GPS based coarse localization, image-level localization, and metric localization has been presented to establish image correspondences between historical and query crack images. Then historical crack pixels can be mapped onto the query crack image, and these mapped crack pixels are seen as high-quality seed points for crack analysis. Finally, crack analysis is accomplished by applying Region Growing Method (RGM) to further detect newly grown cracks. The proposed method has been tested with the actual pavement images collected in different time. The F-measure for crack growth is 88.9%, which demonstrates the proposed method has an ability to greatly simplify and enhances crack analysis result.
Highlights
Modern Pavement Management Systems (PMS) are playing more and more important roles in pavement survey, maintenance, and rehabilitation
In PMS, pavement crack analysis, which deals with crack detection and crack growth detection, is a crucial and core task
This paper demonstrates that historical crack data could greatly enhance pavement crack analysis
Summary
Modern Pavement Management Systems (PMS) are playing more and more important roles in pavement survey, maintenance, and rehabilitation. An increasing number of transportation agencies are building and upgrading their PMS to enhance pavement management. In PMS, pavement crack analysis, which deals with crack detection and crack growth detection, is a crucial and core task. With the development of sensor and information technology, crack data can be quickly and automatically collected by vehicle-borne sensors. Many transportation agencies are routinely (e.g., quarterly, semi-annually, annually, etc) using sensor vehicles for pavement image collection. Thereby, how to accurately identify pavement cracks from the collected pavement images is becoming a key technology in automatic crack analysis in PMS
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