scholarly journals Pavement Crack Detection from Hyperspectral Images Using a Novel Asphalt Crack Index

2020 ◽  
Vol 12 (18) ◽  
pp. 3084 ◽  
Author(s):  
Mohamed Abdellatif ◽  
Harriet Peel ◽  
Anthony G. Cohn ◽  
Raul Fuentes
Keyword(s):  
Crack Detection ◽  
Early Stage ◽  
Visible Spectrum ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Surface Material ◽  
Pavement Condition ◽  
The Road ◽  
Road Pavement ◽  
Crack Index

Detection of road pavement cracks is important and needed at an early stage to repair the road and extend its lifetime for maintaining city roads. Cracks are hard to detect from images taken with visible spectrum cameras due to noise and ambiguity with background textures besides the lack of distinct features in cracks. Hyperspectral images are sensitive to surface material changes and their potential for road crack detection is explored here. The key observation is that road cracks reveal the interior material that is different from the worn surface material. A novel asphalt crack index is introduced here as an additional clue that is sensitive to the spectra in the range 450–550 nm. The crack index is computed and found to be strongly correlated with the appearance of fresh asphalt cracks. The new index is then used to differentiate cracks from road surfaces. Several experiments have been made, which confirmed that the proposed index is effective for crack detection. The recall-precision analysis showed an increase in the associated F1-score by an average of 21.37% compared to the VIS2 metric in the literature (a metric used to classify pavement condition from hyperspectral data).

scholarly journals COMPARATIVE EVALUATION OF PAVEMENT CRACK DETECTION USING KERNEL-BASED TECHNIQUES IN ASPHALT ROAD SURFACES

2016 ◽  
Vol XLI-B1 ◽  
pp. 689-694 ◽  
Author(s):  
A. Miraliakbari ◽  
S. Sok ◽  
Y. O. Ouma ◽  
M. Hahn
Keyword(s):  
Comparative Evaluation ◽  
Crack Detection ◽  
Pavement Condition ◽  
Pavement Distress ◽  
The Road ◽  
Road Pavement ◽  
Segmentation Methods ◽  
Increasing Demand ◽  
Rotational Invariant ◽  
Pavement Crack Detection

With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and evaluation of the actual road conditions. This is due in part to the resulting large volumes of road pavement data captured through digital surveys, and also to the requirements for rapid data processing and evaluations. In this study, the Canon 5D Mark II RGB camera with a resolution of 21 megapixels is used for the road pavement condition mapping. Even though many imaging and mapping sensors are available, the development of automated pavement distress detection, recognition and extraction systems for pavement condition is still a challenge. In order to detect and extract pavement cracks, a comparative evaluation of kernel-based segmentation methods comprising line filtering (LF), local binary pattern (LBP) and high-pass filtering (HPF) is carried out. While the LF and LBP methods are based on the principle of rotation-invariance for pattern matching, the HPF applies the same principle for filtering, but with a rotational invariant matrix. With respect to the processing speeds, HPF is fastest due to the fact that it is based on a single kernel, as compared to LF and LBP which are based on several kernels. Experiments with 20 sample images which contain linear, block and alligator cracks are carried out. On an average a completeness of distress extraction with values of 81.2%, 76.2% and 81.1% have been found for LF, HPF and LBP respectively.

scholarly journals COMPARATIVE EVALUATION OF PAVEMENT CRACK DETECTION USING KERNEL-BASED TECHNIQUES IN ASPHALT ROAD SURFACES

2016 ◽  
Vol XLI-B1 ◽  
pp. 689-694
Author(s):  
A. Miraliakbari ◽  
S. Sok ◽  
Y. O. Ouma ◽  
M. Hahn
Keyword(s):  
Comparative Evaluation ◽  
Crack Detection ◽  
Pavement Condition ◽  
Pavement Distress ◽  
The Road ◽  
Road Pavement ◽  
Segmentation Methods ◽  
Increasing Demand ◽  
Rotational Invariant ◽  
Pavement Crack Detection

With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and evaluation of the actual road conditions. This is due in part to the resulting large volumes of road pavement data captured through digital surveys, and also to the requirements for rapid data processing and evaluations. In this study, the Canon 5D Mark II RGB camera with a resolution of 21 megapixels is used for the road pavement condition mapping. Even though many imaging and mapping sensors are available, the development of automated pavement distress detection, recognition and extraction systems for pavement condition is still a challenge. In order to detect and extract pavement cracks, a comparative evaluation of kernel-based segmentation methods comprising line filtering (LF), local binary pattern (LBP) and high-pass filtering (HPF) is carried out. While the LF and LBP methods are based on the principle of rotation-invariance for pattern matching, the HPF applies the same principle for filtering, but with a rotational invariant matrix. With respect to the processing speeds, HPF is fastest due to the fact that it is based on a single kernel, as compared to LF and LBP which are based on several kernels. Experiments with 20 sample images which contain linear, block and alligator cracks are carried out. On an average a completeness of distress extraction with values of 81.2%, 76.2% and 81.1% have been found for LF, HPF and LBP respectively.

scholarly journals Automated Pavement Crack Damage Detection Using Deep Multiscale Convolutional Features

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Weidong Song ◽  
Guohui Jia ◽  
Hong Zhu ◽  
Di Jia ◽  
Lin Gao
Keyword(s):  
High Performance ◽  
Crack Detection ◽  
Automated Detection ◽  
Key Factors ◽  
The Road ◽  
Intelligent Maintenance ◽  
Road Pavement ◽  
Maintenance Systems ◽  
High Level ◽  
Pavement Crack Detection

Road pavement cracks automated detection is one of the key factors to evaluate the road distress quality, and it is a difficult issue for the construction of intelligent maintenance systems. However, pavement cracks automated detection has been a challenging task, including strong nonuniformity, complex topology, and strong noise-like problems in the crack images, and so on. To address these challenges, we propose the CrackSeg—an end-to-end trainable deep convolutional neural network for pavement crack detection, which is effective in achieving pixel-level, and automated detection via high-level features. In this work, we introduce a novel multiscale dilated convolutional module that can learn rich deep convolutional features, making the crack features acquired under a complex background more discriminant. Moreover, in the upsampling module process, the high spatial resolution features of the shallow network are fused to obtain more refined pixel-level pavement crack detection results. We train and evaluate the CrackSeg net on our CrackDataset, the experimental results prove that the CrackSeg achieves high performance with a precision of 98.00%, recall of 97.85%, F-score of 97.92%, and a mIoU of 73.53%. Compared with other state-of-the-art methods, the CrackSeg performs more efficiently, and robustly for automated pavement crack detection.

scholarly journals Automatic Road Pavement Assessment with Image Processing: Review and Comparison

2011 ◽  
Vol 2011 ◽  
pp. 1-20 ◽  
Author(s):  
Sylvie Chambon ◽  
Jean-Marc Moliard
Keyword(s):  
Image Processing ◽  
Crack Detection ◽  
State Of The Art ◽  
Civil Infrastructures ◽  
The Road ◽  
Multi Scale ◽  
Road Pavement ◽  
Optical Images ◽  
Detection Approach ◽  
Pavement Crack Detection

In the field of noninvasive sensing techniques for civil infrastructures monitoring, this paper addresses the problem of crack detection, in the surface of the French national roads, by automatic analysis of optical images. The first contribution is a state of the art of the image-processing tools applied to civil engineering. The second contribution is about fine-defect detection in pavement surface. The approach is based on a multi-scale extraction and a Markovian segmentation. Third, an evaluation and comparison protocol which has been designed for evaluating this difficult task—the road pavement crack detection—is introduced. Finally, the proposed method is validated, analysed, and compared to a detection approach based on morphological tools.

scholarly journals Automatic Crack Detection of Road Pavement Based on Aerial UAV Imagery

2019 ◽  
Author(s):  
Farzaneh Dadrasjavan ◽  
Nima Zarrinpanjeh ◽  
Azam Ameri
Keyword(s):  
Crack Detection ◽  
The Road ◽  
Remotely Sensed Imagery ◽  
Road Pavement ◽  
Road Surface Monitoring ◽  
Surface Monitoring ◽  
Key Frames ◽  
On The Road ◽  
Edge Based ◽  
Complicated Task

Road surface monitoring more specifically crack detection on the surface of the road pavement is a complicated task which is found vital due to critical nature of roads as elements of transportation infrastructure. Cracks on the road pavement is detectable using remotely sensed imagery or car mounted platforms. UAV’s are also considered as useful tools for acquiring reliable information about the pavement of the road. In This paper, an automatic method for crack detection on the road pavement is proposed using acquired videos from UAV platform. Selecting key frames and generating Ortho-image, violating non road regions in the scene are removed. Then through an edge based approach hypothesis crack elements are extracted. Afterwards, through SVM based classification true cracks are detected. Developing the proposed method, the generated results show 75% accuracy in crack detection while less than 10% of cracks are omitted.

Practice Analysis of Urban Road Pavement Roughness and Detect of Destruction

2011 ◽  
Vol 250-253 ◽  
pp. 3688-3691
Author(s):  
Jr Hung Peng ◽  
Po Hsun Sung ◽  
Jyh Dong Lin ◽  
Kuang Yi Wei
Keyword(s):  
Management System ◽  
Maintenance Management ◽  
Conservation Strategy ◽  
Road Maintenance ◽  
Pavement Condition ◽  
Urban Road ◽  
The Road ◽  
Road Pavement ◽  
Pavement Roughness ◽  
New Construction

The urban road becoming more perfect, pavement engineering is from new construction to maintenance management. The authorities, from acceptance the new construction turn into survey of the road‘s situation and control of various types of damage and road conditions on time, to maintain a good condition of the road. In this study we use the CCD with the general Global Positioning System to provide GPS coordinates and have a street shooting for each 20m of road, record of the CCD road imaging system, and with GPS coordinates, the street pavement shooting can identify the highest frequency distress type within 100m of the road, and compare with the value of IRI for statistics, considering different distress conditions associated with the International Roughness Index, and to explore the causes. This study has an Urban Road Management System, it divided into road flat index query and pavement condition index query, and user can use this system know the pavement condition every section. The road maintenance unit can be judged by this indicator status of pavement roughness to develop a conservation strategy of each section, reflecting the degree of conservation of each section, making the pavement to maintain a good quality. Urban road maintenance management system is for the each authorities built the road pavement maintenance management system for pavement managers with different levels of management authority, and to assist in the system can provide information for urban roads to do planning, query and management, it is beneficial to the authorities to implementation of urban roads and other road maintenance operations, they can immediately understand the pavement condition.

scholarly journals MAPPING AND ASSESSMENT OF TRAFFIC CONGESTION ON MAJOR ROADS IN MINNA (CASE STUDY OF CHANCHAGA L.G.A)

2017 ◽  
Vol 4 (2) ◽  
pp. 171 ◽  
Author(s):  
Oluibukun Gbenga Ajayi ◽  
Ayodeji Timothy Oluwunmi ◽  
Joseph Olayemi Odumosu ◽  
Taiwo James Adewale
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Networks ◽  
Urban Centre ◽  
Pavement Condition ◽  
The Road ◽  
Road Pavement ◽  
Analysis Of Results ◽  
Narrow Road ◽  
Road Corridors

The level of urbanization in the developing world indicates that more people live in cities now than before. As urbanization increases, road usage also increases proportionately which sometimes introduce some strain to the existing road and as a consequence constitutes some impediments to free traffic flow. The situation described above is on the increase in Chanchaga Local Government Area of Niger State, an urban centre in North Central, Nigeria. In order to investigate the probable causes and degree of severity of this menace, an attempt has been made in this research to investigate and map out the nature of traffic congestion frequently experienced on some selected roads within Chanchaga LGA. These road networks include Kpakungun - Gidan Kwano road, Bosso-Mobil route, Bosso – Mekunkele route, Kpakungun – city gate road and Book roundabout – Mobil Route. Using a 1m Pan-Sharpened spatial resolution IKONOS Image, handheld GPS receivers, and manual traffic count, the traffic patterns of the selected road networks within the study area were assessed and mapped out. A Geo-Database was also designed for the routes which provide information about the road pavement condition, average traffic volume, adjacent land use, etc. Analysis of results and other queries performed revealed that the most probable causes of traffic congestion in Chanchaga LGA include narrow road width, bad road pavement and indiscriminate parking of vehicles along the road corridors, especially by commercial cab drivers. Conclusively, it was observed that the Kpakungun axis of Minna – Bida road is the most congested route of all the road networks considered, closely followed by the Bosso-Mobil Road. The traffic gridlock along these routes is most prominent on Mondays and Wednesdays (around 8 am and 4 pm) and also on Fridays (around 1-4pm). Also, a free traffic flow is often experienced on Saturdays by 8 am which gradually builds into a synchronized flow around the evening time on all the road networks considered.  

scholarly journals EVALUASI KERUSAKAN PERKERASAN LENTUR RUAS TOL JAKARTA-CIKAMPEK DAN ALTERNATIF PENANGANANNYA

2021 ◽  
Vol 4 (4) ◽  
pp. 837
Author(s):  
Hans Hendito ◽  
Anissa Noor Tajudin
Keyword(s):  
Traffic Load ◽  
Pavement Condition ◽  
The Road ◽  
Toll Road ◽  
Road Pavement ◽  
A Value ◽  
Design Life ◽  
Common Causes ◽  
On The Road ◽  
Range Of Values

The most common causes of road damage are the design life of the road that has been passed, waterlogging on the road due to poor drainage, or even traffic load which can cause the service life of the road to be shorter than planned. To find out the conditions on the Jakarta-Cikampek Toll Road. Calculates the value of road pavement conditions calculated using the Indeks Kondisi Perkerasan (IKP) on the Jakarta-Cikampek Toll Road. To find out what kind of treatment we should do for the damage that occurs. The Indeks Kondisi Perkerasan is a quantitative indicator of pavement conditions that has a range of values ranging from 0 – 100, with a value of 0 representing the worst pavement condition while 100 representing the best pavement condition. The IKP method has a level of handling type for each IKP value. According to the IKP guidelines, the type of handling that must be carried out with an average IKP value of 96,32 is routine maintenance. For further research, it’s necessary to conduct a direct survey, so that accurate results can be obtained. It is necessary to study with various methods to be able to compare the level of accuracy of a method. ABSTRAKPenyebab kerusakan jalan yang paling umum adalah umur rencana jalan yang telah dilewati, genangan air pada jalan yang diakibatkan drainase yang buruk, atau bahkan beban lalu lintas yang berlebihan yang dapat menyebabkan umur pakai jalan akan menjadi lebih pendek daripada perencanaannya. Untuk mengetahui kondisi pada jalan Tol Jakarta-Cikampek. Menghitung nilai kondisi perkerasan jalan jika dihitung dengan Indeks Kondisi Perkerasan (IKP) pada ruas Tol Jakarta-Cikampek. Untuk mengetahui penanganan seperti apa yang harus kita lakukan terhadap kerusakan yang terjadi. Kondisi Perkerasan atau IKP adalah indikator kuantitatif (numerik) kondisi perkerasan yang mempunyai rentang nilai mulai 0 – 100, dengan nilai 0 nya menyatakan kondisi perkerasan paling jelek sementara 100 menyatakan kondisi perkerasan terbaik. Metode IKP memiliki tingkat jenis penanganan tiap nilai IKP. Menurut pedoman IKP, jenis penanganan yang harus dilakukan dengan nilai IKP rata-rata 96,32 adalah pemeliharaan rutin. Untuk penelitian selanjutnya, perlu untuk survei secara langsung, supaya hasil yang didapat lebih maksimal. Perlu diteliti dengan metode yang beragam untuk dapat membandingkan tingkat keakuratan sebuah metode.

scholarly journals Sensitivity Analysis of Determining the Material Parameters of an Asphalt Pavement to Measurement Errors in Backcalculations

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 873
Author(s):  
Paweł Tutka ◽  
Roman Nagórski ◽  
Magdalena Złotowska ◽  
Marek Rudnicki
Keyword(s):  
Fatigue Life ◽  
Measurement Errors ◽  
Pavement Condition ◽  
Material Parameters ◽  
The Road ◽  
Nondestructive Tests ◽  
Road Pavement ◽  
Falling Weight ◽  
Pavement Reinforcement ◽  
The Impact

Nondestructive tests of road pavements are among the most widely used methods of pavement condition diagnostics. Deflections of road pavement under a known load are most commonly measured in such tests, e.g., with the use of falling weight deflectometer (FWD). Measured values allow to determine the material parameters of the road structure, corresponding to the obtained results, by means of backcalculations. Among the factors that impact on the quality of results is the accuracy of deflection measurement. Deflection basins with small differences of displacement values may correspond to significantly different combinations of material parameters. Taking advantage of them for mechanistic calculations of road pavement may eventually lead to incorrect estimation of the remaining fatigue life and then inadequate selection of pavement reinforcement. This study investigated the impact of measurement errors on the change of the obtained values of stiffness moduli of flexible road pavement layers. Additionally, the influence of obtained material parameters on the values of key pavement strain, and consequently on its design fatigue life was presented.

scholarly journals Analysis of the Damage of Rigid Pavement Road by Using Pavement Condition Index (PCI)

2020 ◽  
Vol 1 (2) ◽  
pp. 193-202
Author(s):  
Muhammad Isradi ◽  
Zaenal Arifin ◽  
Asep Sudrajat
Keyword(s):  
Good Condition ◽  
Industrial Area ◽  
Condition Index ◽  
Rigid Pavement ◽  
Pavement Condition ◽  
The Road ◽  
Road Pavement ◽  
Road Users ◽  
Repair Costs ◽  
Pavement Condition Index

Bogasari Road, which is located in Citeureup sub-district, Bogor Regency, within the PT Indocement Tunggal Prakarsa industrial area, is a road that uses rigid pavement. The road is always passed by heavily loaded vehicles that affect road pavement conditions and the level of comfort and safety for road users. The study's purpose is to determine the average daily traffic volume, determine the value of conditions in the rigid pavement, and provide input to relevant agencies in terms of solutions and road repair costs. The method used in the analysis is the Pavement Condition Index (PCI). The study shows the average daily traffic of 2,883 vehicles/hour/day and the average pavement condition value of 66.57 with a good rating, or in good condition. It also provides a method of repair by functional means.

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