The problem of road sign detection and recognition is very important in many practical problems, above all for road cadastral authorities. In this sense, an automatic application able to identify the kind of a road sign starting from common imageries such as photos could be very helpful. The main difficulty is due to a possible poor graphical definition of the imagery. In this case, a valid support can be provided by the use of Hough Transform. In this paper, our aim is to propose the implementation of a valid, automatic, robust and reliable decisional support to technicians. It is based on the use of the Standard Hough Transform in order to detect the shape, i.e. the macro-class, of road sign (e.g. circular, squared, triangular, etc.). Subsequently, the road sign characterization has been refined by using the generalization of the Hough Transform in order to detect the specific sign within its previously established macro-class.

Automatic Recognition of Road Signs by Hough Transform

BARRILE, Vincenzo;MORABITO, Francesco Carlo
2008

Abstract

The problem of road sign detection and recognition is very important in many practical problems, above all for road cadastral authorities. In this sense, an automatic application able to identify the kind of a road sign starting from common imageries such as photos could be very helpful. The main difficulty is due to a possible poor graphical definition of the imagery. In this case, a valid support can be provided by the use of Hough Transform. In this paper, our aim is to propose the implementation of a valid, automatic, robust and reliable decisional support to technicians. It is based on the use of the Standard Hough Transform in order to detect the shape, i.e. the macro-class, of road sign (e.g. circular, squared, triangular, etc.). Subsequently, the road sign characterization has been refined by using the generalization of the Hough Transform in order to detect the specific sign within its previously established macro-class.
Road sign detection, Hough Transform, Road cadastral, Image processing, GIS, Mobile mapping
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/4787
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