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dc.contributor.advisorBiswas, Rubel
dc.contributor.advisorMostakim, Moin
dc.contributor.authorPinku, Subroto Nag
dc.date.accessioned2016-05-22T11:01:36Z
dc.date.available2016-05-22T11:01:36Z
dc.date.copyright2016
dc.date.issued4/20/2016
dc.identifier.otherID 11201019
dc.identifier.urihttp://hdl.handle.net/10361/5304
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 50-51).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2016.en_US
dc.description.abstractTraffic signs play a vital role in transportation system. Many road accidents occur due to over speed. Detecting and classifying different group of Speed limit traffic signs can save our lives as well as resources. In this research we propose a novel approach towards the detection of these signs. In our proposed system with the help of color and non-color information of traffic signs we first detect the presence of a sign and the classify it. For detection we used circle Hough transformation along with segmentation and labeling. After extracting sign from a scene we match the sign against a classified dataset. We used deformable spatial pyramid matching for recognition of the sign. Once we find a match, our system returns the class or speed limit. Our experiment shows that the recognition rate is very high and we compare our result with another approach at the end.en_US
dc.description.statementofresponsibilitySubroto Nag Pinku
dc.format.extent51 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectComputer science and engineeringen_US
dc.subjectCSEen_US
dc.subjectTraffic sign recognitionen_US
dc.titleSpeed limit traffic sign recognition in night mode based on deformable spatial pyramiden_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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