Image‐Processing Techniques Applied to Road Problems
Publication: Journal of Transportation Engineering
Volume 118, Issue 1
Abstract
Relevant areas of image‐processing applications were reviewed, and several initial investigations were carried out to assess the potential of applying digital imaging techniques to road problems. The areas chosen were: Road surface rating, measurement, and discrimination; calibrated sieve measurement; vehicle outline detection; and vehicle registration number recognition. Practical selective video data‐acquisition equipment was built and tested as a result of this investigation. Analysis of the characteristics of road and traffic applications showed that these and other steps need to be taken to reduce the quantity of unnecessary images being collected for analysis. Effective test results were obtained in most of these trial areas, and the conclusions are that adaptive Laws masks show promise for defect classification, automatic detection of speed and shape classification is practical, sieve mensuration and calibration is a practical objective, vehicle number recognition may require ancillary equipment, road surface defects could be addressed directly, and discrimination of road surfaces and their condition may be addressed. This paper includes a review of the various image processing methods available for invariant moment analysis and surface‐texture discrimination and classification, and concludes that Laws masks are currently the preferred technique.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Ade, F. (1981). “Characterization of textures by eigenfliters.” Signal Processing, 5, 451.
2.
Abu‐Mostafa, Y. S., and Psaltis, D. (1984). “Image normalization by complex moments.” IEEE Trans. Pattern Analysis and Machine Intelligence PAMI‐7(1), 46–55.
3.
Ahlers, K. D., and Alexander, D. R. (1985). “Microcomputer based digital image processing system developed to count and size laser generated small particle images.” Optical Engrg., 24(6), 1060–1065.
4.
Barlow, H. B. (1969). “Pattern Recognition and the responses of sensory neurons.” Ann. N.Y. Acad. Sci., 156, 822–881.
5.
Benke, K. K. (1986). “The analysis of visual texture,” thesis, presented to Deakin University, at Geelong, Australia, in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
6.
Brady, M. (1982). “Computational Approaches to Image Understanding.” Comp. Surv., 14(1), 3–71.
7.
Brodatz, F. (1966). Textures: A photographic album for artists and designers. Dover, New York, N.Y.
8.
Casasent, D., and Psaltis, D. (1979). “Optical pattern recognition using invariant moments.” Soc. of Photo‐Optical Instrum. Engineers, (201), 107–114.
9.
Castleman, K. R. (1979). Digital image processing. Prentice Hall, Englewood‐Cliffs, N.J.
10.
Cox, G., Curphey, D., Fronek, D., and Wilson, J. (1986a). “Remote sensing of highway pavements at road speeds: Using the Motorola 68020 Microprocessor.” Microcomputers in Civ. Engrg., 1(1), 1–13.
11.
Cox, G., Merrill, R. C., and Fronek, D. (1986b). “Pavement management system with realtime microprocessor‐based computation.” Microcomputers in Civ. Engrg., 1(2), 95–105.
12.
Dickinson, K. W., and Waterfall, R. C. (1984). “Image processing applied to traffic. 1: General review.” Traffic Engrg. Control, (1), 6–13.
13.
Duff, M. J. B. (1983). Neighborhood operators in biological processes of images. E. J. Braddick and A. C. Sleigh, eds., Springer‐Verlag, Berlin, Germany.
14.
Duncan, J. S., and Frei, W. (1982). “Very large scale integration (VLSI) approach to feature extraction.” SPIE Applications of Digital Image Processing, (4), 359, 378–385.
15.
Gagalowicz, A. (1980). “Visual discrimination of stochastic texture fields based upon their second order statistics.” Proc., 5th Int. Conf. Pattern Recognition, Institute of Electrical and Electronics Engineers, New York, N.Y., 786–788.
16.
Gallagher, V. P., and Lerner, N. (1983). “A model of visual complexity of highway scenes.” Report FHWA/RD‐83/083, U.S. Dept. of Transportation, Washington, D.C.
17.
Gonzalez, R. C., and Wintz, P. (1987). Digital image processing, 2nd ed., Addison‐Wesley, Reading, Mass.
18.
Haas, L., Shen, H., Phang, W. A., and Haas, R. (1985). “Application of imag eanalysis technology to automation of pavement condition surveys. Transportation towards the year 2000.” Proc., Int. Transp. Congress RTAC, Ottawa, Canada, (5)C57–C72.
19.
Haralick, R. M. (1984). “Digital step edges from zero crossings of second directional derivatives.” IEEE Trans. Pattern Analysis and Machine Intelligence, PAMI‐6, 58–68.
20.
Harwood, D., Subbarao, M., and Davis, L. S. (1983). “Texture classification by local rank order correlation.” TR‐1314, Computer Vision Laboratory, Center for Automation Research, University of Maryland, Baltimore, Md.
21.
Hu, M.‐K. (1962). “Visual pattern recognition by invariant moments.” IRE Trans. on Info. Theory, 8(Feb.), 179–187.
22.
Hubel, P. H., and Wiesel, T. N. (1962). “Receptive fields, binocular interaction and functional architecture in the cats visual cortex.” Physiology, London, England, (160), 106–154.
23.
Hsia, T. C. (1981). “A note on invariant moments in image processing.” IEEE Trans. on Systems Man and Cybernetics SMC‐11, (12), 871–874.
24.
Laws, K. I. (1980). “Textured image segmentation.” Tech. Report 940, Image Processing Institute, University of Southern California, Los Angeles, Calif.
25.
Maitra, S. (1979). “Moment Invariants.” Proc., IEEE, 67(4), 697–699.
26.
Marr, D. (1982). Vision. W. H. Freeman and Co., San Francisco, Calif.
27.
McClelland, J. L., and Rumelhart, D. E. (1988). Explorations in parallel distributed processing. MIT Press, Cambridge, Mass.
28.
Newlands, D. A. (1985). “Image reconstruction from moment series,” thesis presented to Deakin University, Geelong, Australia, in partial fulfillment of the requirements for the degree of Bachelor of Science.
29.
Pentland, A. P. (1984). “Fractal‐based description of natural scenes.” IEEE Trans. Pattern Analysis and Machine Intelligence, PAMI‐6, 661–674.
30.
Teague, M. R. (1980). “Image analysis via the general theory of moments.” J. Optical Soc. America, 70(8), 920–30.
31.
Triendl, E. E. (1972). “Automatic terrain mapping by texture recognition.” Proc., 8th Int. Symp. on Remote Sensing of Environment, Environmental Research Institute of Michigan, Ann Arbor, Mich.
32.
Van Gool, L., Dewaele, P., and Oosterlinck, A. (1985). “Texture analysis Anno 1983.” Computer Vision, Graphics and Image Processing, (29), 336–357.
33.
Vickers, A. L., and Modestino, J. W. (1982). “A maximum‐likelihood approach to texture classification.” IEEE Trans. Pattern Analysis and Machine Intelligence PAMI‐4, 1, 61–68.
34.
Wechlser, H., and Kidode, M., (1980). “A random walk procedure for texture discrimination.” IEEE Trans. Pattern Analysis and Machine Intelligence PAMI‐1, 3, 272–280.
35.
Wermser, D., and Liedtke, C. E. (1982). “Texture analysis using a model of the visual system.” Proc., 6th Int. Conf. on Pattern Recognition, Munich, Germany, 1078–1080.
36.
Wigan, M. R. (1983). “Information technology and transport: Research proposals.” Technical Note TN126. Institute for Transport Studies, University of Leeds, England.
37.
Wigan, M. R. (1985a). Image processing for roads: An on‐line literature review and text data base assessment. Australian Road Res., Melbourne, Australia, 15(1), 50–55.
38.
Wigan, M. R. (1985tb). “The potential for computer based data logging and interpretation.” Proc., Pavement Management Systems Workshop, Australian Road Research Board, Vermont, Australia, 65–71.
39.
Wigan, M. R. (1986). “Selective road and traffic data acquisition (SDA) for roads and traffic and video capture control.” Internal Report AIR 413‐3, Australian Road Research Board, Vermont, Australia.
40.
Wigan, M. R., and Cullinan, M. C. (1984). “Machine vision for road research: New tasks and old problems.” Proc., 12th ARRB Conf., Vermont, Australia, 12(4), 76–86.
41.
Wigan, M. R., and Cullinan, M. C. (1986). “Digital image processing: An applications review for road research applications.” Proc., 2nd AUSGRAPH Conf., Australian Computer Graphics Association, Melbourne, Australia, 57–60.
42.
Wigan, M. R., and Cullinan, M. C. (1987). “Image processing applied to roads: Surface texture, mensuration, vehicle shape and number detection.” Res. Report ARR 145, Australian Road Research Board, Vermont, Australia.
43.
Yin, B. H., and Mack, H. (1981). “Target classification algorithms for video and forward looking improved (FLIR) imaging.” Soc. Photo‐Optical Instrument Engineers, (302), 134–140.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 118 • Issue 1 • January 1992
Pages: 62 - 83
Copyright
Copyright © 1992 ASCE.
History
Published online: Jan 1, 1992
Published in print: Jan 1992
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.