The extraction of pavement cracks is always a hard task in image processing.In airport and road construction,cracking is the main factor for pavement damage,which can decrease the quality of pavement and affect transp...The extraction of pavement cracks is always a hard task in image processing.In airport and road construction,cracking is the main factor for pavement damage,which can decrease the quality of pavement and affect transportation seriously.Cracks also exist in other artificial or natural objects,such as buildings,bridges,tunnels,etc.Among all the object images,pavement crack images are the most complex,so the image processing and analysis for them is harder than other crack images.From the early image acquisition based on photography technology to the current 3 D laser scanning technology,the pavement crack image acquisition technology is becoming more convenient and efficient,but there are still challenges in the automatic processing and recognition of cracks in images.From the early global thresholding to deep learning algorithms,the research for crack extraction has been developed for about 40 years.There are many methods and algorithms that are satisfactory in pavement crack applications,but there is no standard until today.Therefore,in order to know the developing history and the advanced research,we have collected a number of literature in this research topic for summarizing the research artwork status,and giving a review of the pavement crack image acquisition methods and2 D crack extraction algorithms.Also,for image acquisition methods and pavement crack image segmentation,more detailed comparison and discussions are made.展开更多
In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers a...In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.展开更多
基金financially supported by the National Natural Science Fund in China(grant No.61170147)the National Natural Science Key Fund in China(grant No.U1401252).
文摘The extraction of pavement cracks is always a hard task in image processing.In airport and road construction,cracking is the main factor for pavement damage,which can decrease the quality of pavement and affect transportation seriously.Cracks also exist in other artificial or natural objects,such as buildings,bridges,tunnels,etc.Among all the object images,pavement crack images are the most complex,so the image processing and analysis for them is harder than other crack images.From the early image acquisition based on photography technology to the current 3 D laser scanning technology,the pavement crack image acquisition technology is becoming more convenient and efficient,but there are still challenges in the automatic processing and recognition of cracks in images.From the early global thresholding to deep learning algorithms,the research for crack extraction has been developed for about 40 years.There are many methods and algorithms that are satisfactory in pavement crack applications,but there is no standard until today.Therefore,in order to know the developing history and the advanced research,we have collected a number of literature in this research topic for summarizing the research artwork status,and giving a review of the pavement crack image acquisition methods and2 D crack extraction algorithms.Also,for image acquisition methods and pavement crack image segmentation,more detailed comparison and discussions are made.
基金supported by the National Key R&D Program of China(2017YFF0205600)the International Research Cooperation Seed Fund of Beijing University of Technology(2018A08)+1 种基金Science and Technology Project of Beijing Municipal Commission of Transport(2018-kjc-01-213)the Construction of Service Capability of Scientific and Technological Innovation-Municipal Level of Fundamental Research Funds(Scientific Research Categories)of Beijing City(PXM2019_014204_500032).
文摘In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.
