AUTOMATED PAVEMENT IMAGING PROGRAM (APIP) FOR PAVEMENT CRACKS 
CLASSIFICATION AND QUANTIFICATION - A PHOTOGRAMMETRIC APPROACH 
M. Mustaffar 3 *, T. C. Ling b , O. C. Puan b 
Purveying Unit, Faculty of Civil Engineering, Universiti Teknologi Malaysia - mushairry@yahoo.com 
b Dept. of Geotechnics and Transportation, Universiti Teknologi Malaysia 
Commission VI, WG IV/3 
KEY WORDS: APIP, Image processing, Photogrammetry, Pavement distress, Cracks, Potholes, Delaminatons 
ABSTRACT: 
The evaluation of pavement conditions is an important part of pavement management. Traditionally, pavement condition data are 
gathered by human inspectors who walk or drive along the road to assess the distresses and subsequently produce report sheets. This 
visual survey method is not only time consuming and costly but more importantly it compromises the safety of the field personnel. 
With an automated digital image processing technique, however, pavement distress analysis can be conducted in a swifter and safer 
manner. Pavement distresses are captured on images which are later automatically analysed. Furthermore, the automated method can 
improve the objectivity, accuracy, and consistency of the distress survey data. This research is aimed at the development of an 
Automated Pavement Imaging Program (APIP) for evaluating pavement distress condition. The digital image processing program 
enables longitudinal, transverse, and alligator cracking to be classified. Subsequently, the program will automatically estimate the 
crack intensity which can be used for rating pavement distress severity. Advancement in digital photogrammetric technology creates 
an opportunity to overcome some problems associated with the manual methods. It can provide a low-cost, near real time 
geometrical imaging through digital photogrammetry without physically touching the surface being measured. Moreover, digital 
photogrammetry workstation (DPW) is user-friendly, less tedious and enables surface conditions to be represented as ortho-image, 
overlay contour with ortho-image, as well as digital elevation model.-The algorithms developed in this study are found to be capable 
of identifying type of cracking and its severity level with an accuracy of about 90% when compared to the traditional method. This 
is to show that the combination of the photogrammetric approach and APIP is a viable system to be used in pavement evaluations. 
1. INTRODUCTION 
Pavement distresses are visible imperfections on the surface of 
the pavements. Therefore, the evaluation of pavement condition 
is an important part to provide information to keep pavements 
in good condition. Accurate evaluations would result in a better 
chance that resources will be distributed normally. Thus, 
yielding a better service condition (Kim, 1998). Pavement can 
be evaluated through the different types of distress experienced, 
such as cracking, disintegration and surface deformation. At 
present, there are various methods of conducting distress 
surveys, recording and analysing distress survey data (Cheng 
and Miyojim, 1998). Pavement engineers have long recognized 
the importance of distress information in quantifying the quality 
of pavements. This information has been used to document 
present pavement condition, chart past performance history, and 
predict future pavement performance. 
2. PROBLEM STATEMENT 
Manual visual inspection of pavement surface condition is 
costly and time consuming. In many cases, work has to be done 
along fast moving traffic. Such condition would endanger the 
safety of the personnel involved. In the wake of tedious manual 
measurements and safety issues, various types of automated 
equipments have been developed for the purpose of pavement 
monitoring and evaluation. 
Visual observation of pavement distress is the most common 
method for monitoring pavement surface condition. This has 
been traditionally performed by trained engineers who work or 
drive along the road and counts the distresses (Oh, 1998). 
However 
this method of field inspection poses several 
drawbacks, such as: 
(i) 
Slow, labour intensive and expensive. 
(ii) 
Subjective approach generating inconsistencies 
and inaccuracies in the determination of pavement 
condition. 
(hi) 
Inflexible and does not provide an absolute 
measure of the surface. 
(iv) 
Has poor repeatability since the assessment of 
given pavement section may be differ from one 
survey to the next. 
(V) 
Could expose a serious safety hazard to the 
surveyors due to high speed and high volume 
traffic. 
Numerous system users believe that there is a need to minimise 
the drawbacks listed above, replacing manual data collection 
system with automated systems. In response to these demands, 
various studies have been conducted to apply new technologies 
in pavement monitoring. Among these technologies, close- 
range digital photogrammetry is seen as a possible approach in 
providing accurate, consistent data and easy visualisation for 
pavement distress studies. Furthermore, a combination of a 
close-range digital photogrammetry data collection system with 
a suitable image processing analysis would result in a system 
that is reliable and dependable. Therefore, this study looks at 
developing a photogrammetric based pavement evaluation 
approach by utilising ortho-images and image processing 
techniques. 
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