This paper describes a method for detecting and recognizing road signs in grey-level images acquired by a single camera mounted on a moving vehicle. An extensive experimentation has shown that the method is robust against low-level noise corrupting edge detection and contour following, and works for images of cluttered urban streets as well as country roads and highways. A further improvement on the detection and recognition scheme has been obtained by means of a Kalman-filter-based temporal integration of the extracted information. The proposed approach can be very helpful for the development of a system for driving assistance.

Robust road sign detection and recognition from image sequences

De Micheli Enrico;
1994

Abstract

This paper describes a method for detecting and recognizing road signs in grey-level images acquired by a single camera mounted on a moving vehicle. An extensive experimentation has shown that the method is robust against low-level noise corrupting edge detection and contour following, and works for images of cluttered urban streets as well as country roads and highways. A further improvement on the detection and recognition scheme has been obtained by means of a Kalman-filter-based temporal integration of the extracted information. The proposed approach can be very helpful for the development of a system for driving assistance.
1994
Istituto di Biofisica - IBF
Inglese
Intelligent Vehicles '94 Symposium
278
283
6
0-7803-2135-9
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=639527
24-26 October
Paris (F)
Road sign detection
Image sequences
Recognition
1
none
Piccioli Giulia; De Micheli Enrico; Parodi Piero; Campani Marco
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/1022
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