Koha online

Your cart is empty.
Normal view MARC view ISBD view

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

by Escalera, Sergio [author.]; Baró, Xavier [author.]; Pujol, Oriol [author.]; Vitrià, Jordi [author.]; Radeva, Petia [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Computer Science: Publisher: London : Springer London, 2011.Description: VI, 96p. 34 illus. online resource.ISBN: 9781447122456.Subject(s): Computer science | Computer vision | Computer Science | Image Processing and Computer VisionDDC classification: 006.6 | 006.37 Online resources: Click here to access online
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.
Tags from this library: No tags from this library for this title. Add tag(s)
Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Call number Status Date due Barcode
TA1637-1638 (Browse shelf) Available
Long Loan MAIN LIBRARY
TA1637-1638 (Browse shelf) Available

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.

There are no comments for this item.

Log in to your account to post a comment.
@ Jomo Kenyatta University Of Agriculture and Technology Library

Powered by Koha