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Digital image processing techniques for pavement macro-texture analysis

Elunai, Ronald, Chandran, Vinod, & Mabukwa, Prosper (2010) Digital image processing techniques for pavement macro-texture analysis. In Doyle, Neil (Ed.) Proceedings of the 24th ARRB Conference: Building on 50 years of road transport research, ARRB Group Ltd., Sebel Hotel, Melbourne, Vic, pp. 1-5.

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Abstract

Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

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ID Code: 40770
Item Type: Conference Paper
Keywords: Conferences, Evaluation, Image Processing, Pavements, Skid Resistance, Texture
ISSN: 0572-1431
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2010 [please consult the Authors]
Deposited On: 29 Mar 2011 08:04
Last Modified: 01 Mar 2012 13:16

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