By Topic

Identifying and retrieving distress images from road pavement surveys

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

This paper proposes a system capable of identifying and retrieving distress images from a road pavement survey image database. A database of images acquired during road pavement surface surveys along Portuguese roads is considered. Regions corresponding to cracks are detected over the acquired images, based on a subdivision of the images into a set of non-overlapping windows, which may be classified as containing cracks, or not. Crack detection results, represented by binary images where windows containing crack pixels are set to one, undergo a second classification stage to distinguish several crack types. This classification follows the structure proposed by the Portuguese Distresses Catalog, produced by the national entity in charge of road maintenance. Three crack types are identified at this stage: longitudinal cracks, transversal cracks and miscellaneous cracks. The experimental results, obtained by processing real survey imagery over Portuguese roads, present encouraging results for automating the process of identifying road distresses from images.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008