Road traffic sign detection and classification

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Road traffic sign detection and classification

A vision-based vehicle guidance system for road vehicles can have three main roles: 1) road detection; 2) obstacle detection; and 3) sign recognition. The first two have been studied for many years and with many good results, but traffic sign recognition is a less-studied field. Traffic signs provide drivers with very valuable information about the road, in order to make driving safer and easie...

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Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I as well as I2V) applications are developing very fast. They rely on telecommunication and localization technologies to detect, identify and geo-localize the sources of information (such as vehicles, roadside objects, or pedestrians). This paper presents an original approach on how two different technologies (a near infrared identificat...

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A semi-automatic traffic sign detection, classification, and positioning system

The availability of large-scale databases containing street-level panoramic images offers the possibility to perform semi-automatic surveying of real-world objects such as traffic signs. These inventories can be performed significantly more efficiently than using conventional methods. Governmental agencies are interested in these inventories for maintenance and safety reasons. This paper introd...

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Road Sign Detection and Recognition

Road sign detection is important to a robotic vehicle that automatically drives on roads. In this paper, road signs are detected by means of rules that restrict color and shape and require signs to appear only in limited regions in an image. They are then recognized using a template matching method and tracked through a sequence of images. The method is fast and can easily be modified to includ...

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Road-sign detection and tracking

In a visual driver-assistance system, road-sign detection and tracking is one of the major tasks. This study describes an approach to detecting and tracking road signs appearing in complex traffic scenes. In the detection phase, two neural networks are developed to extract color and shape features of traffic signs from the input scenes images. Traffic signs are then located in the images based ...

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ژورنال

عنوان ژورنال: IEEE Transactions on Industrial Electronics

سال: 1997

ISSN: 0278-0046

DOI: 10.1109/41.649946