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Real-time radial symmetry for speed sign detection

dc.contributor.authorBarnes, Nick
dc.contributor.authorZelinsky, Alex
dc.coverage.spatialParma Italy
dc.date.accessioned2015-12-13T22:49:13Z
dc.date.createdJune 14 2004
dc.date.issued2004
dc.date.updated2015-12-11T10:33:01Z
dc.description.abstractAlgorithms for classifying road signs have a high computational cost per pixel processed. A promising approach to real-time sign detection is to reduce the number of pixels to be classified as being a particular sign to a minimum by some form of sign detection on the image using less time expensive algorithms. In this paper, we adapt the fast radial symmetry detector to the image stream from a camera mounted in a car eliminate almost all non-sign pixels from the image stream. We then are able to apply normalised cross-correlation to classify the signs. This method is suitable for circular signs only; we apply it to Australian speed signs in this paper. Our results show that it is robust to a broad range of lighting conditions. Also, as the method is fast, there is no need to make unrealistically strict assumptions about image structure.
dc.identifier.isbn0780383109
dc.identifier.urihttp://hdl.handle.net/1885/80433
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE Intelligent Vehicles Symposium 2004
dc.sourceProceedings of the IEEE Intelligent Vehicles Symposium
dc.subjectKeywords: Cameras; Charge coupled devices; Edge detection; Illuminating engineering; Image processing; Intelligent vehicle highway systems; Real time systems; Roads and streets; Simulated annealing; Color segmentation; Road signs; Sign recognition; Speed signs; Tra
dc.titleReal-time radial symmetry for speed sign detection
dc.typeConference paper
local.bibliographicCitation.lastpage571
local.bibliographicCitation.startpage566
local.contributor.affiliationBarnes, Nick, College of Engineering and Computer Science, ANU
local.contributor.affiliationZelinsky, Alex, College of Engineering and Computer Science, ANU
local.contributor.authoruidBarnes, Nick, a176407
local.contributor.authoruidZelinsky, Alex, u9615131
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080101 - Adaptive Agents and Intelligent Robotics
local.identifier.ariespublicationMigratedxPub8695
local.identifier.scopusID2-s2.0-4544283098
local.type.statusPublished Version

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