19.6.3.9.1 Inspection -- Pavement, Road Surface, Asphalt, Concrete

Chapter Contents (Back)
Pavement Analysis. Crack Detection. Application, Inspection. Inspection, Defects. Defect Detection.

Kalliomäki, I.[Ilkka], Vehtari, A.[Aki], Lampinen, J.[Jouko],
Shape analysis of concrete aggregates for statistical quality modeling,
MVA(16), No. 3, May 2005, pp. 197-201.
Springer DOI 0505
BibRef

Le Bastard, C., Baltazart, V., Wang, Y., Saillard, J.,
Thin-Pavement Thickness Estimation Using GPR With High-Resolution and Superresolution Methods,
GeoRS(45), No. 8, August 2007, pp. 2511-2519.
IEEE DOI 0709
BibRef

Bourlier, C., Le Bastard, C., Baltazart, V.,
Generalization of PILE Method to the EM Scattering From Stratified Subsurface With Rough Interlayers: Application to the Detection of Debondings Within Pavement Structure,
GeoRS(53), No. 7, July 2015, pp. 4104-4115.
IEEE DOI 1503
Ground penetrating radar BibRef

Yamaguchi, T.[Tomoyuki], Hashimoto, S.[Shuji],
Fast crack detection method for large-size concrete surface images using percolation-based image processing,
MVA(21), No. 5, August 2010, pp. 797-809.
WWW Link. 1011
BibRef
Earlier:
Improved percolation-based method for crack detection in concrete surface images,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Clemmensen, L.H.[Line H.], Hansen, M.E.[Michael E.], Ersbøll, B.K.[Bjarne K.],
A comparison of dimension reduction methods with application to multi-spectral images of sand used in concrete,
MVA(21), No. 6, October 2010, pp. 959-968.
WWW Link. 1011
BibRef

Fujita, Y.[Yusuke], Hamamoto, Y.[Yoshihiko],
A robust automatic crack detection method from noisy concrete surfaces,
MVA(22), No. 2, March 2011, pp. 245-254.
WWW Link. 1103
BibRef

Elunai, R., Chandran, V., Gallagher, E.,
Asphalt Concrete Surfaces Macrotexture Determination From Still Images,
ITS(12), No. 3, September 2011, pp. 857-869.
IEEE DOI 1109
BibRef

Li, Q.Q.[Qing-Quan], Zou, Q.[Qin], Zhang, D.Q.[Da-Qiang], Mao, Q.Z.[Qing-Zhou],
FoSA: F* Seed-growing Approach for crack-line detection from pavement images,
IVC(29), No. 12, November 2011, pp. 861-872.
Elsevier DOI 1112
Line detection; Pavement crack; Seed-growing; Dynamic programming BibRef

Zou, Q.[Qin], Cao, Y.[Yu], Li, Q.Q.[Qing-Quan], Mao, Q.Z.[Qing-Zhou], Wang, S.[Song],
CrackTree: Automatic crack detection from pavement images,
PRL(33), No. 3, 1 February 2012, pp. 227-238.
Elsevier DOI 1201
Crack detection; Edge detection; Edge grouping; Tensor voting; Shadow removal BibRef

Suanpaga, W., Yoshikazu, K.,
Riding Quality Model for Asphalt Pavement Monitoring Using Phase Array Type L-band Synthetic Aperture Radar (PALSAR),
RS(2), No. 11, November 2010, pp. 2531-2546.
DOI Link 1203
BibRef

Ndoye, M., Barker, A.M., Krogmeier, J.V., Bullock, D.M.,
A Recursive Multiscale Correlation-Averaging Algorithm for an Automated Distributed Road-Condition-Monitoring System,
ITS(12), No. 3, September 2011, pp. 795-808.
IEEE DOI 1109
BibRef

Oliveira, H., Correia, P.L.,
Automatic Road Crack Detection and Characterization,
ITS(14), No. 1, March 2013, pp. 155-168.
IEEE DOI 1303
BibRef

Fang, H., Lin, G., Zhang, R.,
The First-Order Symplectic Euler Method for Simulation of GPR Wave Propagation in Pavement Structure,
GeoRS(51), No. 1, January 2013, pp. 93-98.
IEEE DOI 1301
BibRef

Shangguan, P.C.[Peng-Cheng], Al-Qadi, I.L.,
Calibration of FDTD Simulation of GPR Signal for Asphalt Pavement Compaction Monitoring,
GeoRS(53), No. 3, March 2015, pp. 1538-1548.
IEEE DOI 1412
asphalt BibRef

Guan, H.[Haiyan], Li, J., Yu, Y.T.[Yong-Tao], Chapman, M., Wang, H.[Hanyun], Wang, C.[Cheng], Zhai, R.F.[Rui-Fang],
Iterative Tensor Voting for Pavement Crack Extraction Using Mobile Laser Scanning Data,
GeoRS(53), No. 3, March 2015, pp. 1527-1537.
IEEE DOI 1412
crack detection See also Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data. BibRef

Yi, C., Chuang, Y., Nian, C.,
Toward Crowdsourcing-Based Road Pavement Monitoring by Mobile Sensing Technologies,
ITS(16), No. 4, August 2015, pp. 1905-1917.
IEEE DOI 1508
Feature extraction BibRef

Rajamohan, D.[Deepak], Gannu, B.[Bhavana], Rajan, K.S.[Krishnan Sundara],
MAARGHA: A Prototype System for Road Condition and Surface Type Estimation by Fusing Multi-Sensor Data,
IJGI(4), No. 3, 2015, pp. 1225.
DOI Link 1508
BibRef

Mathavan, S., Kamal, K., Rahman, M.,
A Review of Three-Dimensional Imaging Technologies for Pavement Distress Detection and Measurements,
ITS(16), No. 5, October 2015, pp. 2353-2362.
IEEE DOI 1511
Survey, Pavement Analysis. computer vision BibRef

Quintana, M., Torres, J., Menéndez, J.M.,
A Simplified Computer Vision System for Road Surface Inspection and Maintenance,
ITS(17), No. 3, March 2016, pp. 608-619.
IEEE DOI 1603
Cameras BibRef

Zhang, S.[Su], Lippitt, C.D.[Christopher D.], Bogus, S.M.[Susan M.], Neville, P.R.H.[Paul R. H.],
Characterizing Pavement Surface Distress Conditions with Hyper-Spatial Resolution Natural Color Aerial Photography,
RS(8), No. 5, 2016, pp. 392.
DOI Link 1606
BibRef

Hoult, N.A., Dutton, M., Hoag, A., Take, W.A.,
Measuring Crack Movement in Reinforced Concrete Using Digital Image Correlation: Overview and Application to Shear Slip Measurements,
PIEEE(104), No. 8, August 2016, pp. 1561-1574.
IEEE DOI 1608
Area measurement BibRef

Khan, S.M., Atamturktur, S., Chowdhury, M., Rahman, M.,
Integration of Structural Health Monitoring and Intelligent Transportation Systems for Bridge Condition Assessment: Current Status and Future Direction,
ITS(17), No. 8, August 2016, pp. 2107-2122.
IEEE DOI 1608
Bridges BibRef

Amhaz, R.[Rabih], Chambon, S.[Sylvie], Idier, J.[Jerome], Baltazart, V.[Vincent],
Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection,
ITS(17), No. 10, October 2016, pp. 2718-2729.
IEEE DOI 1610
BibRef
Earlier:
A new minimal path selection algorithm for automatic crack detection on pavement images,
ICIP14(788-792)
IEEE DOI 1502
Context Cost function BibRef

Ishikawa, T.[Tsuyoshi], Fujinami, K.[Kaori],
Smartphone-Based Pedestrian's Avoidance Behavior Recognition towards Opportunistic Road Anomaly Detection,
IJGI(5), No. 10, 2016, pp. 182.
DOI Link 1610
BibRef

Jang, D.W., Park, R.H.,
Pothole detection using spatio-temporal saliency,
IET-ITS(10), No. 9, 2016, pp. 605-612.
DOI Link 1609
asphalt BibRef

Shi, Y., Cui, L., Qi, Z., Meng, F., Chen, Z.,
Automatic Road Crack Detection Using Random Structured Forests,
ITS(17), No. 12, December 2016, pp. 3434-3445.
IEEE DOI 1612
Feature extraction BibRef

Zaini, N.[Nasrullah], van der Meer, F.[Freek], van Ruitenbeek, F.[Frank], de Smeth, B.[Boudewijn], Amri, F.[Fadli], Lievens, C.[Caroline],
An Alternative Quality Control Technique for Mineral Chemistry Analysis of Portland Cement-Grade Limestone Using Shortwave Infrared Spectroscopy,
RS(8), No. 11, 2016, pp. 950.
DOI Link 1612
BibRef

Zhang, D.[Dejin], Li, Q.Q.[Qing-Quan], Chen, Y.[Ying], Cao, M.[Min], He, L.[Li], Zhang, B.L.[Bai-Ling],
An efficient and reliable coarse-to-fine approach for asphalt pavement crack detection,
IVC(57), No. 1, 2017, pp. 130-146.
Elsevier DOI 1702
Pavement crack detection BibRef

Casselgren, J.[Johan], Bodin, U.[Ulf],
Reusable road condition information system for traffic safety and targeted maintenance,
IET-ITS(11), No. 4, May 2017, pp. 230-238.
DOI Link 1705
BibRef

Lenglet, C.[Céline], Blanc, J.[Juliette], Dubroca, S.[Stéphane],
Smart road that warns its network manager when it begins cracking,
IET-ITS(11), No. 3, April 2017, pp. 152-157.
DOI Link 1705
BibRef

González, L.C., Moreno, R., Escalante, H.J., Martínez, F., Carlos, M.R.,
Learning Roadway Surface Disruption Patterns Using the Bag of Words Representation,
ITS(18), No. 11, November 2017, pp. 2916-2928.
IEEE DOI 1711
Accelerometers, Automobiles, Data collection, Roads, Sensors, Smart phones, Urban areas, Roadway surface disruptions, accelerometer. BibRef

Chen, Q.[Qusen], Jiang, W.P.[Wei-Ping], Meng, X.L.[Xiao-Lin], Jiang, P.[Peng], Wang, K.[Kaihua], Xie, Y.[Yilin], Ye, J.[Jun],
Vertical Deformation Monitoring of the Suspension Bridge Tower Using GNSS: A Case Study of the Forth Road Bridge in the UK,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Carmon, N.[Nimrod], Ben-Dor, E.[Eyal],
Mapping Asphaltic Roads' Skid Resistance Using Imaging Spectroscopy,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Pérez, J.P.C.[Juan Pedro Cortés], de Sanjosé Blasco, J.J.[José Juan], Atkinson, A.D.J.[Alan D. J.], del Río Pérez, L.M.[Luis Mariano],
Assessment of the Structural Integrity of the Roman Bridge of Alcántara (Spain) Using TLS and GPR,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Zhang, B.[Bochen], Ding, X.[Xiaoli], Werner, C.[Charles], Tan, K.[Kai], Zhang, B.[Bin], Jiang, M.[Mi], Zhao, J.W.[Jing-Wen], Xu, Y.[Youlin],
Dynamic displacement monitoring of long-span bridges with a microwave radar interferometer,
PandRS(138), 2018, pp. 252-264.
Elsevier DOI 1804
Structural health monitoring (SHM), Dynamics, Displacements, Microwave radar interferometer, Long-span bridge BibRef

Matarazzo, T.J., Santi, P., Pakzad, S.N., Carter, K., Ratti, C., Moaveni, B., Osgood, C., Jacob, N.,
Crowdsensing Framework for Monitoring Bridge Vibrations Using Moving Smartphones,
PIEEE(106), No. 4, April 2018, pp. 577-593.
IEEE DOI 1804
Bridges, Inspection, Public infrastructure, Smart buildings, Smart cities, Smart phones, Urban areas, Vibrations, Big Data, Wireless Sensor Networks BibRef

Carlos, M.R., Aragón, M.E., González, L.C., Escalante, H.J., Martínez, F.,
Evaluation of Detection Approaches for Road Anomalies Based on Accelerometer Readings: Addressing Who's Who,
ITS(19), No. 10, October 2018, pp. 3334-3343.
IEEE DOI 1810
Roads, Accelerometers, Sensors, Support vector machines, Proposals, Acceleration, Accelerometer measurements, mobile sensing, road anomalies BibRef


Song, W., Workman, S., Hadzic, A., Zhang, X., Green, E., Chen, M., Souleyrette, R., Jacobs, N.,
FARSA: Fully Automated Roadway Safety Assessment,
WACV18(521-529)
IEEE DOI 1806
image processing, neural nets, road safety, roads, traffic engineering computing, FARSA, US Road Assessment Program, Training BibRef

Liu, X., Ai, Y., Scherer, S.,
Robust image-based crack detection in concrete structure using multi-scale enhancement and visual features,
ICIP17(2304-2308)
IEEE DOI 1803
Indexes, Crack detection, concrete structure, guided filter, image enhancement BibRef

Güldür Erkal, B., Apaydin, N.M.,
Bridge Surface Damage Detection Application with A Laser-based Software Prototype,
GeoAdvances17(55-57).
DOI Link 1805
BibRef

Grünauer, A.[Andreas], Halmetschlager-Funek, G.[Georg], Prankl, J.[Johann], Vincze, M.[Markus],
Learning the Floor Type for Automated Detection of Dirt Spots for Robotic Floor Cleaning Using Gaussian Mixture Models,
CVS17(576-589).
Springer DOI 1711
BibRef

Chaudhury, S., Nakano, G., Takada, J., Iketani, A.,
Spatial-Temporal Motion Field Analysis for Pixelwise Crack Detection on Concrete Surfaces,
WACV17(336-344)
IEEE DOI 1609
Bridges, Concrete, Labeling, Loading, Maintenance engineering, Safety, Surface cracks. BibRef

Martínez-Sánchez, J., Puente, I., GonzálezJorge, H., Riveiro, B., Arias, P.,
Automatic Thickness And Volume Estimation Of Sprayed Concrete On Anchored Retaining Walls From Terrestrial Lidar Data,
ISPRS16(B5: 521-526).
DOI Link 1610
BibRef

Abdic, I., Fridman, L., Brown, D.E., Angell, W., Reimer, B., Marchi, E., Schuller, B.,
Detecting road surface wetness from audio: A deep learning approach,
ICPR16(3458-3463)
IEEE DOI 1705
Cameras, Data collection, Recurrent neural networks, Roads, Rough surfaces, Spectrogram, Tires BibRef

Vandoni, J., Le Hégarat-Mascle, S., Aldea, E.,
Crack detection based on a Marked Point Process model,
ICPR16(3933-3938)
IEEE DOI 1705
Adaptation models, Data models, Extremities, Image segmentation, Joining processes, Roads, Robustness BibRef

Zhang, Z., Hamada, O., Toda, H., Akiduki, T., Miyake, T.,
Study on bridge floor crack detection using the 2-dimensional complex discrete wavelet packet transform,
ICWAPR16(225-229)
IEEE DOI 1611
Bridges BibRef

Liu, Y.H.[Ya-Hui], Yao, J.[Jian], Liu, K.[Kang], Lu, X.[Xiaohu], Xia, M.[Menghan],
Optimal Image Stitching For Concrete Bridge Bottom Surfaces Aided By 3d Structure Lines,
ISPRS16(B3: 527-534).
DOI Link 1610
BibRef

Zhang, L., Yang, F., Zhang, Y.D.[Y. Daniel], Zhu, Y.J.,
Road Crack Detection Using Deep Convolutional Neural Network,
ICIP16(3708-3712)
IEEE DOI 1610
Boosting BibRef

Miraliakbari, A., Sok, S., Ouma, Y.O., Hahn, M.,
Comparative Evaluation Of Pavement Crack Detection Using Kernel-based Techniques In Asphalt Road Surfaces,
ISPRS16(B1: 689-694).
DOI Link 1610
BibRef

Knyaz, V.A., Chibunichev, A.G.,
Photogrammetric Techniques For Road Surface Analysis,
ISPRS16(B5: 515-520).
DOI Link 1610
BibRef

Chen, X.[Xinqu], Li, J.[Jonathan],
A Feasibility Study On Use Of Generic Mobile Laser Scanning System For Detecting Asphalt Pavement Cracks,
ISPRS16(B1: 545-549).
DOI Link 1610
BibRef

Choi, J., Zhu, L., Kurosu, H.,
Detection Of Cracks In Paved Road Surface Using Laser Scan Image Data,
ISPRS16(B1: 559-562).
DOI Link 1610
BibRef

Uus, A., Liatsis, P., Slabaugh, G., Anagnostis, A., Roberts, S., Twist, S.,
Trend deviation analysis for automated detection of defects in GPR data for road condition surveys,
WSSIP16(1-4)
IEEE DOI 1608
asphalt BibRef

Uus, A., Liatsis, P., Nardoni, G., Rahman, E.,
Optimisation of transducer positioning in air-coupled ultrasound inspection of concrete/asphalt structures,
WSSIP15(309-312)
IEEE DOI 1603
asphalt BibRef

Miah, S., Uus, A., Liatsis, P., Roberts, S., Twist, S., Hovens, M., Godding, H.,
Design of multidimensional sensor fusion system for road pavement inspection,
WSSIP15(304-308)
IEEE DOI 1603
ground penetrating radar BibRef

Masiero, A., Guarnieri, A., Pirotti, F., Vettore, A.,
Semi-Automated Detection of Surface Degradation on Bridges Based on a Level Set Method,
Laser15(15-21).
DOI Link 1602
BibRef

Fernandes, K.[Kelwin], Ciobanu, L.[Lucian],
Pavement pathologies classification using graph-based features,
ICIP14(793-797)
IEEE DOI 1502
Feature extraction BibRef

Medina, R.[Roberto], Llamas, J.[Jose], Zalama, E.[Eduardo], Gomez-Garcia-Bermejo, J.[Jaime],
Enhanced automatic detection of road surface cracks by combining 2D/3D image processing techniques,
ICIP14(778-782)
IEEE DOI 1502
Cameras BibRef

Miraliakbari, A., Hahn, M., Maas, H.G.,
Development of a Multi-Sensor System for Road Condition Mapping,
LandImaging14(265-272).
DOI Link 1411
BibRef

Xu, W.[Wei], Tang, Z.M.[Zhen-Min], Zhou, J.[Jun], Ding, J.D.[Jun-Di],
Pavement crack detection based on saliency and statistical features,
ICIP13(4093-4097)
IEEE DOI 1412
Bayesian model; Crack detection; saliency map; statistical feature BibRef

Mulsow, C.,
Determination of the Degree of Gravel Aggregate-Bitumencoverage by Multi-Directional Reflectance Measurements,
ISPRS12(XXXIX-B5:39-43).
DOI Link 1209
BibRef

Aoki, K., Yamamoto, K., Shimamura, H.,
Evaluation Model for Pavement Surface Distress On 3d Point Clouds From Mobile Mapping System,
ISPRS12(XXXIX-B3:87-90).
DOI Link 1209
BibRef

Salari, E., Yu, X.,
Pavement distress detection and classification using a Genetic Algorithm,
AIPR11(1-5).
IEEE DOI 1204
BibRef

Kallen, H.[Hanna], Heyden, A.[Anders], Astrom, K.[Kalle], Lindh, P.[Per],
Measurement of bitumen coverage of stones for road building, based on digital image analysis,
WACV12(337-344).
IEEE DOI 1203
Pavement inspection. BibRef

Tong, X.H.[Xu-Hang], Guo, J.[Jie], Ling, Y.[Yun], Yin, Z.P.[Zhou-Ping],
A new image-based method for concrete bridge bottom crack detection,
IASP11(568-571).
IEEE DOI 1112
BibRef

Detchev, I.[Ivan], Habib, A.[Ayman], El-Badry, M.[Mamdouh],
Estimation Of Vertical Deflections In Concrete Beams Through Digital Close Range Photogrammetry,
Laser11(xx-yy).
DOI Link 1109
BibRef

Oliveira, H.[Henrique], Caeiro, J.J.[Jose Jasnau], Correia, P.L.[Paulo Lobato],
Improved road crack detection based on one-class Parzen density estimation and entropy reduction,
ICIP10(2201-2204).
IEEE DOI 1009
BibRef

Avila, M.[Manuel], Begot, S.[Stephane], Duculty, F.[Florent], Nguyen, T.S.[Tien Sy],
2D image based road pavement crack detection by calculating minimal paths and dynamic programming,
ICIP14(783-787)
IEEE DOI 1502
BibRef
And: A4, A2, A3, A1:
Free-form anisotropy: A new method for crack detection on pavement surface images,
ICIP11(1069-1072).
IEEE DOI 1201
Continuous wavelet transforms BibRef

Yuan, X.[Xia], Zhao, C.X.[Chun-Xia], Cai, Y.F.[Yun-Fei], Zhang, H.F.[Hao-Feng], Chen, D.B.[De-Bao],
Road-surface abstraction using ladar sensing,
ICARCV08(1097-1102).
IEEE DOI 1109
BibRef

Yoshida, H.[Hiromi], Tanaka, N.[Naoki],
A Binarization Method for Crack Detection in a Road Surface Image with the Fractal Dimension,
MVA09(70-).
PDF File. 0905
BibRef

Zhang, C.[Chunsun],
An UAV-based Photogrammetric Mapping System for Road Condition Assessment,
ISPRS08(B5: 627 ff).
PDF File. 0807
BibRef

Oliveira, H.[Henrique], Correia, P.L.[Paulo Lobato],
Identifying and retrieving distress images from road pavement surveys,
ICIP08(57-60).
IEEE DOI 0810
BibRef

Li, Q.Q.[Qing-Quan], Liu, X.L.[Xiang-Long],
A Model for Segmentation and Distress Statistic of Massive Pavement Images Based on Multi-Scale Strategies,
ISPRS08(B5: 63 ff).
PDF File. 0807
BibRef

Subirats, P., Dumoulin, J., Legeay, V., Barba, D.,
Automation of Pavement Surface Crack Detection using the Continuous Wavelet Transform,
ICIP06(3037-3040).
IEEE DOI 0610
BibRef

Hansen, M.E.[Michael E.], Ersbøll, B.K.[Bjarne K.], Carstensen, J.M.[Jens M.], Nielsen, A.A.[Allan A.],
Estimation of Critical Parameters in Concrete Production Using Multispectral Vision Technology,
SCIA05(1228-1237).
Springer DOI 0506
BibRef

Fujita, Y.[Yusuke], Mitani, Y.[Yoshihiro], Hamamoto, Y.[Yoshihiko],
A Method for Crack Detection on a Concrete Structure,
ICPR06(III: 901-904).
IEEE DOI 0609
BibRef

Zhang, T.[Tong], Nagy, G.,
Surface tortuosity and its application to analyzing cracks in concrete,
ICPR04(II: 851-854).
IEEE DOI 0409
BibRef

Nagy, G.[George], Zhang, T.[Tong], Franklin, W.R., Landis, E.[Eric], Nagy, E.[Edwin], Keane, D.T.[Denis T.],
Volume and Surface Area Distributions of Cracks in Concrete,
VF01(759 ff.).
Springer DOI 0209
BibRef

Cho, S.H., Hisatomi, K., Hashimoto, S.,
Cracks and Displacement Feature Extraction of the Concrete Block Surface,
MVA98(xx-yy). BibRef 9800

Tanaka, N., Uematsu, K.,
A Crack Detection Method in Road Surface Images Using Morphology,
MVA98(xx-yy). BibRef 9800

Bursanescu, L.,
Automated Pavement Distress Collection and Analysis,
3DIM97(12 - Applications) 9702
BibRef

Delagnes, P., Barba, D.,
A Markov random field for rectilinear structure extraction in pavement distress image analysis,
ICIP95(I: 446-449).
IEEE DOI 9510
BibRef

Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Inspection -- Paint and Printing Quality, Print Analysis .


Last update:Nov 17, 2018 at 09:12:27