Image‐Processing Techniques Applied to Road Problems

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.