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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Traffic-Sign Recognition Systems

Traffic-Sign Recognition Systems

Escalera, Sergio
Baró, Xavier
Pujol, Oriol

Paperback

Series: Springerbriefs in Computer Science

General ComputersProgramming

ISBN10: 1447122445
ISBN13: 9781447122449
Publisher: Springer Nature
Published: Sep 23 2011
Pages: 96
Weight: 0.35
Height: 0.22 Width: 6.14 Depth: 9.21
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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