Abstract
This research examined pavement video images collected through application of video imaging system. A low-cost pavement imaging system using video technique was developed. To collect pavement video images, a field test was performed by the developed system. As a result of the video test runs, seven test loops were selected for further image analysis. The collected video images were processed by digital image processing to evaluate pavement condition. The calculated crack index values were analyzed by statistical technique to analyze repeatability of images and to identify significant variables. ANOVA tests for each seven-test loop showed that there was poor repeatability for AC and PCC images. The variable effects were tested using general linear model analysis. As a result of analysis, the significant variables for AC and PCC pavement images were identified.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Digital Vision Inc.,ComputerEyes/1024—Owners Manual, 1995.
El-Korchi, T. and Wittels, N., Visual Appearance of Surface Distress in PCC Pavements: I. Crack Luminance,Transportation Research Record 1260, Transportation Research Board, 1990.
Guralnick, S. A., Suen, E. S., and Zoruba, S., Development of Automated Road Inspection Vehicle for Nondestructive Evaluation of Road Surface Condition,Transportation Research Record 1536, Transportation Research Board, 1996.
Hanley, R. C. and Larsen, D. A., The Connecticut Photolog Laser Videodisc-Based Pavement Rating System,Journal of Transportation Engineering, ASCE, Vol. 118, No. 2, March/April, 1992.
Jain, A. K.,Fundamentals of Digital Image Processing, Prentice Hall, 1989.
Jitprasithsiri, S., Lee, H., Sorcic, R. C., and Johnston, R.,Development of a Digital Image Processing Algorithm to Compute a Unified Crack Index for Salt Lake City, Transportation Research Board, Washington D.C., 1996.
Kalikiri, V. K., Garrick, N. W., and Achenie, L. E. K., Image-Processing Methods for Automated Distress Evaluation,Transportation Research Record 1435, Transportation Research Board, 1994.
Kim, J.,Development of a Low-Cost Video Imaging System for Pavement Evaluation, PhD. Dissertation, Civil Engineering, Oregon State University, 1997.
Kleinbaum, D. G., Kupper, L. L., Muller, K. E., and Nizam, A.,Applied Regression Analysis and Other Multivariable Methods, Duxbury Press, 1997.
Koutsopoulos, H. and Downey, A.B., Primitive-Based Classification of Pavement Cracking Images,Journal of Transportation Engineering, ASCE, Vol. 119, No. 3, May/June, 1993.
Koutsopoulos, H., and El Sanhouri, I., Methods and Algorithms for Automated Analysis of Pavement Images,Transportation Research Record 1311, Transportation Research Board, 1991.
Landphair, H. C. and Larsen, T. R., Applications of 3-D and 4-D Visualization Technology in Transportation,NCHRP Synthesis 229, Transportation Research Board, 1996.
Ritchie, S. G., Digital Imaging Concepts and Applications in Pavement Management,Journal of Transportation Engineering, ASCE, Vol. 116, No. 3, May/June, 1990.
Sahoo, P. K., Soltani, S., and Wong, A. K. C., A survey of thresholding techniques,Computer Vision, Graphics, and Image Processing, 41, pp 233–260, 1988.
SAS/STAT User’s Guide, Version 6, Forth Edition, Vol. 2, SAS Institute Inc., 1990.
Smith, R. E., Freeman T. J., and Pendelton, O. J.,Evaluation of Automated Pavement Distress Data Collection Procedures for Local Agency Pavement Management, Texas Transportation Institute, Texas A&M University, July 1996.
Author information
Authors and Affiliations
Corresponding author
Additional information
The manuscript for this paper was submitted for review on January 24, 2000.
Rights and permissions
About this article
Cite this article
Kim, J. Statistical analysis of video images for evaluating pavement distress. KSCE J Civ Eng 4, 257–264 (2000). https://doi.org/10.1007/BF02823974
Issue Date:
DOI: https://doi.org/10.1007/BF02823974