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Traffic-Sign Recognition Systems [electronic resource] / by Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Computer SciencePublisher: London : Springer London, 2011Description: VI, 96p. 34 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781447122456
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.6 23
  • 006.37 23
LOC classification:
  • TA1637-1638
  • TA1637-1638
Online resources:
Contents:
Introduction -- Background on Traffic Sign Detection and Recognition -- Traffic Sign Detection -- Traffic Sign Categorization -- Traffic Sign Detection and Recognition System -- Conclusions.
In: Springer eBooksSummary: 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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Item type Current library Call number Status Date due Barcode
E-Book E-Book Central Library Available E-39210

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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