Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/462078
Title: Enhancing the Accuracy in Traffic Sign Detection using Classification Algorithms
Researcher: KARTHIKA, R
Guide(s): MURUGAN S
Keywords: Computer Science
Computer Science Theory and Methods
Engineering and Technology
University: Bharathidasan University
Completed Date: 2020
Abstract: Data mining is extracting information from large sets of databases or data newlinesets. Data mining is the process of discovering correlations, patterns, trends, or newlinerelationships by divine through ahuge amount of knowledge stored in repositories, newlinecorporate databases, and data warehouses. newlineTraffic signs are road facilities that convey, guide, restrict, warn, or instruct newlineinformation using words or symbols. If the drivers and pedestrians donot notice this newlineinformation, this may cause the occurrence of traffic accidents. With the increasing newlinedemand for the intelligence of vehicles, it is extremely necessary to detect and newlinerecognize traffic signs automatically through technology. Research in this area began newlinein 1980s, to unravel this problem. To make them easy for drivers to read and newlinerecognize traffic signs are often designed to be of a specific shape and color with a newlinerobust number 50 .These features also are important information for traffic sign newlinerecognition systems.However, traffic sign recognition isnot a simple task, because newlinethere are many adverse factors, like inclemency, viewpoint variation, physical newlinedamage, etc. The difficulty is detecting the traffic signs are as follows: newlineAlthough an equivalent quite traffic signs has some consistency in color, in newlineoutdoor environments the color of the traffic signs is greatly influenced by newlineillumination and lightweight direction. Therefore, the color information isnot fully newlinereliable. newlineTraffic signs in some road scenes are often obscured by buildings, trees, and newlineother vehicles, therefore, would have liked to acknowledge the traffic signs with newlineincomplete information. newlinexi newlineTraffic sign discoloration, traffic sign damage, rain,snow, fog and other newlineproblems, also are given as challenges within the process of traffic sign detection and newlineclassification. The various condition dark shade light, blurring,fading, rainy and newlineFoggy. newlineAt present many of the existing Text mining algorithms are applied only for newlinethe entire images to detect the traffic sign images. There is no centroid p
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URI: http://hdl.handle.net/10603/462078
Appears in Departments:Department of Computer Science and Applications

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3. con.pdf8.1 kBAdobe PDFView/Open
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5. cha 1.pdf226.54 kBAdobe PDFView/Open
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