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Feature Points for Traffic Sign Detection and Recognition System Using ANFIS

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dc.contributor.author Phu, Kay Thinzar
dc.contributor.author Oo, Lwin Lwin
dc.date.accessioned 2019-07-03T08:06:14Z
dc.date.available 2019-07-03T08:06:14Z
dc.date.issued 2018-02-22
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/319
dc.description.abstract The reliable traffic sign detection provides to achieve performance in traffic sign recognition. Features representation is an important factor for TSDR system. The purpose of this research is to propose an adaptive threshold method based on RGB color for detection and extracting new feature points for traffic sign recognition. In this system, the RGB color based adaptive threshold method is used to detect red, blue and yellow traffic signs. Output traffic signs perform shape verification. Second, new feature points are extracted from the verified image, such as centroid point, end point, and branch point. Finally, ANFIS is used to identify the process. This system uses Myanmar Traffic Sign dataset. en_US
dc.language.iso en en_US
dc.publisher Sixteenth International Conferences on Computer Applications(ICCA 2018) en_US
dc.title Feature Points for Traffic Sign Detection and Recognition System Using ANFIS en_US
dc.type Article en_US


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