Stereo-vision applications to reconstruct the 3D texture of pavement surface

References

• Ahammed , M.A. and Tighe , S. 2008 . “ Incorporation of surface texture, skid resistance and noise ” . In 7th International conference on managing pavement assets Calgary, Alberta
   Google Scholar
• American Concrete Pavement Association (ACPA), 2000. Concrete pavement surface texture, A special report in Concrete Pavement Technology and Research, SR902P
   Google Scholar
• American Society for Testing and Materials, Standards Designations, 2005. Road and paving materials; vehicle-pavement systems. Annual Book of ASTM Standards, E1845, E965-96, E2157
   Google Scholar
• Bennett , J.M. and Mattsson , L. 1999 . Introduction to surface roughness and scattering , 2nd ed. , Optical Society of America, Washington, DC .
   Google Scholar
• Britton , S.C. , Ledbetter , W.B. and Gallaway , B.M. 1974 . Estimation of skid numbers from surface texture parameters in the rational design of standard reference pavements for test equipment calibration . Journal of Testing and Evaluation , 2 ( 2 ) : 73 – 83 .
   Web of Science ®Google Scholar
• Coleman , E.N. Jr and Jain , R. 1982 . Obtaining 3-dimensional shape of textured and specular surface using four-source photometry . Computer Graphics and Image Processing , 18 : 309 – 328 .
   Google Scholar
• Dana , K.J. 1999 . Reflectance and texture of real world surfaces . ACM Transactions on Graphics (TOG) , 18 ( 1 ) : 1 – 34 .
   Web of Science ®Google Scholar
• Dana , K.J. and Nayar , S.K. 1999 . Correlation model for 3D texture . IEEE International Conference on Computer Vision (ICCV) , 2 : 1061 – 1066 .
   Google Scholar
• De León , E. and Flintsch , G.W. 2006 . Application of digital image to measure hot mix asphalt homogeneity . Journal of the Association of Asphalt Paving Technologists , 76 : 41 – 58 .
   Google Scholar
• El Gendy , A. and Shalaby , A. 2007a . Improved specularity detection relying on a photometric stereo technique . Graphics, Vision, and Image Processing, GVIP, The International Congress for Global Science and Technology (ICGST) , 6 ( 4 ) : 39 – 46 .
   Google Scholar
• El Gendy , A. and Shalaby , A. 2007b . Mean profile depth of pavement surface macrotexture using photometric stereo techniques . Journal of Transportation Engineering, American Society of Civil Engineers (ASCE) , 133 ( 7 ) : 433 – 440 .
   Web of Science ®Google Scholar
• El Gendy , A. and Shalaby , A. 2007c . “ Pavement texture classification using two dimensional Fourier transform of image-based recovered surface ” . In CSCE 2007 Annual General Meeting & Conference June 6–9, Yellowknife, Canada
   Google Scholar
• El Gendy , A. and Shalaby , A. 2008 . Image requirements for 3D measurements of pavement macrotexture . Journal of the Transportation Research Board , : 126 – 134 . No. 2068, Transportation Research Record, Washington, DC
   Google Scholar
• El Gendy, A., 2009. Characterization of pavement surface texture using photometric stereo techniques, Thesis (PhD). University of Manitoba, Canada
   Google Scholar
• Flintsch , G.W. , McGhee , K.K. and de León , E. 2005 . Field validation of macrotexture-based hot mix asphalt segregation detection methods . Journal of the Association of Asphalt Paving Technologists , 74 : 1 – 21 .
   Google Scholar
• Flintsch , G. 2008 . “ Area-based macrotexture measurements using stereo vision ” . In 6th Symposium on Pavement Surface Characteristics (SURF) Portoro, Slovenia
   Google Scholar
• Gransberg , D. , Karaca , I. and Burketi , W. 2002 . Quantifying seal coat surface condition using digital image processing based on information theory . International Journal of Pavement Engineering , 3 ( 4 ) : 197 – 205 .
   Google Scholar
• Gransberg , D. 2005 . “ Measuring chip seal texture with digital imagery ” . In Surface friction international conference Christchurch, New Zealand
   Google Scholar
• Gullón, C., 2003. Height recovery of rough surfaces from intensity images, Thesis (PhD). Heriot-Watt University, Edinburgh, Scotland
   Google Scholar
• Hryciw , R.D. and Raschke , S.A. 1996 . Development of computer vision technique for in situ soil characterization . Transportation Research Record 1526 , : 86 – 97 . TRB, National Research Council, Washington, DC
   Google Scholar
• International Organization for Standardization (ISO), 1997. GPS – surface texture: profile method, terms, definitions and surface texture parameters. International Standard No. 4287
   Google Scholar
• International Organization for Standardization (ISO), 1997. Characterization of pavement texture by use of surface profiles, part 1: Determination of mean profile depth. International Standard No. 13473-1
   Google Scholar
• Kuo, C.-Y., et al., 1996. Three-dimensional image analysis of aggregate particles from orthogonal projections. Transportation Research Record 1526, TRB, National Research Council, Washington, DC, pp. 98–103
   Google Scholar
• Masad, E., et al., 2001. Correlation of fine aggregate imaging shape indices with asphalt mixture performance. Transportation Research Record 1757, TRB, National Research Council, Washington, DC, pp. 148–156
   Google Scholar
• McGunnigle, G., 1998. The classification of textured surfaces under varying illuminant direction, Thesis (PhD). Heriot-Watt University, Edinburgh, Scotland, pp. 998
   Google Scholar
• Nayar , S.K. and Oren , M. 1995 . Visual appearance of matte surfaces . Science , 267 : 1153 – 1156 .
   PubMedGoogle Scholar
• National Concrete Pavement Technology Center (NCPTC) . 2006 . Evaluation of U.S. and European concrete pavement noise reduction methods Part 1, Task2, of the ISU-FHWA project, Iowa State University, 2711 South Loop Drive, Suite 4700, Ames, IA 50010
   Google Scholar
• Olek , J. , Weiss , W.J. and García-Villareal , R. 2004 . Relating surface texture of rigid pavements with noise and skid resistance Purdue, West Lafayette
   Google Scholar
• Rao, C. and Tutumluer, E., 2000. Determination of volume of aggregates: new image-analysis approach. Transportation Research Record 1721, TRB, National Research Council, Washington, DC, pp. 73–80
   Google Scholar
• Rasmussen, R., et al., 2008. Identifying quieter concrete pavements using on-board sound intensity. 87th Annual meeting of the Transportation Research Board, Washington, DC
   Google Scholar
• Schonfeld, R., 1970. Photo-interpretation of skid resistance. Highway Research Record: No. 311 Pavement slipperiness, roughness, and condition evaluation, National Research Council, Washington, DC, pp. 11–25
   Google Scholar
• Viner, H., Sinhal, R., and Parry, T., 2004. Review of UK skid resistance policy. 5th Symposium on Pavement Surface Characteristics, Toronto, Canada
   Google Scholar
• Woodham , R. 1980 . Photometric method for determining surface orientation from multiple images . Optical Engineering , 19 : 139 – 144 .
   Web of Science ®Google Scholar
• Zhang , R. 1999 . Shape from shading: a survey . IEEE Transactions on Pattern Analysis and Machine Intelligence , 21 ( 8 ) : 690 – 706 .
   Google Scholar
• Zhao , J. and Katupitiya , J. 2006 . “ A dynamic programming approach based stereo vision algorithm improving object border performance ” . In Proceedings: IEEE/RSJ international conference on Intelligent Robots and Systems October, Beijing, China
   Google Scholar
• Zimmerman , K. and Larson , R. 2005 . Improving safety as part of a pavement preservation program . Transportation Research Circular E-C078 , : 159 – 172 . Transportation Research Board of the National Academies, Washington, DC
   Google Scholar