Traffic-Sign Recognition Systems

Nonfiction, Computers, Advanced Computing, Engineering, Optical Data Processing, Application Software, Computer Graphics, General Computing
Cover of the book Traffic-Sign Recognition Systems by Petia Radeva, Sergio Escalera, Oriol Pujol, Jordi Vitrià, Xavier Baró, Springer London
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Author: Petia Radeva, Sergio Escalera, Oriol Pujol, Jordi Vitrià, Xavier Baró ISBN: 9781447122456
Publisher: Springer London Publication: September 22, 2011
Imprint: Springer Language: English
Author: Petia Radeva, Sergio Escalera, Oriol Pujol, Jordi Vitrià, Xavier Baró
ISBN: 9781447122456
Publisher: Springer London
Publication: September 22, 2011
Imprint: Springer
Language: English

This work presents a full generic approach to the detection and recognition of traffic signs. The approach 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 research and continuing challenges.

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This work presents a full generic approach to the detection and recognition of traffic signs. The approach 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 research and continuing challenges.

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