Traffic-Sign Recognition Systems: SpringerBriefs in Computer Science
Autor Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radevaen Limba Engleză Paperback – 23 sep 2011
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Specificații
ISBN-13: 9781447122449
ISBN-10: 1447122445
Pagini: 101
Ilustrații: VI, 96 p. 34 illus.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.16 kg
Ediția:2011
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
ISBN-10: 1447122445
Pagini: 101
Ilustrații: VI, 96 p. 34 illus.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.16 kg
Ediția:2011
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science
Locul publicării:London, United Kingdom
Public țintă
ResearchCuprins
Introduction.- Background on Traffic Sign Detection and Recognition.- Traffic Sign Detection.- Traffic Sign Categorization.- Traffic Sign Detection and Recognition System.- Conclusions.
Textul de pe ultima copertă
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.
Caracteristici
Presents a full generic approach to the detection and recognition of traffic signs, based on state-of-the-art computer vision methods for object detection, and on powerful methods for multiclass classification Surveys a specific methodology for the problem of traffic sign categorization: Error-Correcting Output Codes Includes experimental validation results performed on a mobile mapping application Includes supplementary material: sn.pub/extras