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Traffic-Sign Recognition Systems

by Escalera, Sergio.
Authors: Baró, Xavier.%author. | Pujol, Oriol.%author. | Vitrià, Jordi.%author. | Radeva, Petia.%author. | SpringerLink (Online service) Series: SpringerBriefs in Computer Science, 2191-5768 Physical details: VI, 96p. 34 illus. online resource. ISBN: 1447122453 Subject(s): Computer science. | Computer vision. | Computer Science. | Image Processing and Computer Vision.
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E-Book E-Book AUM Main Library 006.6 (Browse Shelf) Not for loan

Introduction -- Background on Traffic Sign Detection and Recognition -- Traffic Sign Detection -- Traffic Sign Categorization -- Traffic Sign Detection and Recognition System -- Conclusions.

This work presents a full generic approach to the detection and recognition of traffic signs. The approach, originally developed for a mobile mapping application, is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization – Error-Correcting Output Codes – and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future lines of research, and continuing challenges for traffic sign recognition.

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