Image analysis and intelligent transport
Center adviser
Studies image processing, artificial intelligence and intelligent transport, including image-based inspection of asphalt pavement cracks.
Listed separately from selected publications. Record type and available evidence are stated for each item.
2014 · Published conference paper · NCCE 2014
Develops the Laser MPD: DRR prototype to measure pavement mean profile depth as an indicator for friction screening and network-level road safety assessment.
Published research, with a short guide to the question and method.
8 selected publications
IEEE JCSSE 2018, pp. 1–6
Studies detection of the exposed cut ends of eucalyptus logs from images taken behind loaded timber trucks.
Journal of Image and Graphics, 4(1), pp. 46–50
Combines colour, shape and line analysis to identify buildings or visible building parts in street-level images.
6th ATRANS Symposium: Young Researcher’s Forum, pp. 255–260
Presents prototype equipment for assessing mean pavement profile depth to support maintenance planning.
International Conference on Highway Engineering, Bangkok, 18–20 May 2012
Investigates semi-automatic faulting algorithms for highway engineering; the institutional bibliography verifies the conference work.
2009 International Conference on Computer Engineering and Technology, 43–47
Studies motorcycle and license-plate detection through fixed-size vertical projection and multi-part mean analysis. Publisher-deposited metadata verifies the conference publication.
VISAPP 2009, pp. 269–272
Investigates a gravity-inspired image-processing step to separate noise from pavement cracks during segmentation.
4th IEEE International Symposium on Electronic Design, Test and Applications (DELTA 2008), pp. 49–54
Studies enhanced grid-cell analysis for detecting cracks in asphalt-surface images.
2008 Second International Symposium on Intelligent Information Technology Application, 508–512
Investigates traffic warning-sign detection and recognition using fuzzy logic and chain-code analysis. Publisher-deposited metadata verifies the conference publication.
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Selected research outputs follow the original sources, including work at different institutions. Not every item is a current center project.
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