Characterization of road microtexture by means of image analysis

Road-surface microtexture (sub-millimeter scale) is essential for pavement skid-resistance. However, its measurement is only possible in laboratory on cores taken from trafficked roads, and is time consuming. For an efficient road monitoring, it is necessary to develop faster methods and usable on-site. Collaboration has been developed for two years between LCPC and the laboratory Signal, Image and Communication (SIC) to develop a measurement and characterization method for road microtexture based on image analysis. This paper deals with tow complementary works: - The measurement of road microtexture. Research is focused on the image measurement and extraction of roughness information from images. The prototype using a high-resolution camera is described. The procedure separating relief- from aspect-information using a photometric model for the surface is given. Image-based relief variation is compared to relief variation obtained through laser sensor. - The characterization of road microtexture. This characterization, obtained through a geometrical and frequential analysis of images, leads to descriptors related to the shape and the density of surface asperities. Experimental campaigns were carried out to validate the feasibility of measuring on-site images and to correlate surface descriptors to friction. Results are presented and discussed. Perspective for future works is given.

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Additional Info

Field Value
Source 10th International Conference Metrology and Properties of Engineering Surfaces
Author Ben Slimane, Anis, Khoudeir, Madji, Brochard, Jacques, Do, Minh Tan
Maintainer CCSD
Last Updated May 10, 2026, 02:56 (UTC)
Created May 10, 2026, 02:56 (UTC)
Identifier hal-00851279
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor SIGNAL-IMAGE-COMMUNICATION (SIC) ; Université de Poitiers = University of Poitiers (UP)-Centre National de la Recherche Scientifique (CNRS)
coverage Saint-Etienne, France
creator Ben Slimane, Anis
date 2005-07-04T00:00:00
harvest_object_id a7331551-3fcb-4b5b-be84-0ff68f49887a
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2024-01-31T00:00:00
set_spec type:COMM