T. S. Rosenstock ([email protected]) and P. H. Brown, Dept of Plant Sciences, Univ. of California, Davis, Davis, CA 95616, USA. Present address for TSR: Agricultural Sustainability Inst., Univ. of California, Davis, Davis, CA 95616, USA. – A. Hastings and D. J. Lyles, Dept of Environmental Science and Policy, Univ. of California, Davis, Davis, CA 95616, USA. – W. D. Koenig, Lab of Ornitho...

Colour and shape are basic characteristics of traffic signs which are used both by the driver and to develop artificial traffic sign recognition systems. However, these sign features have not been represented robustly in the earlier developed recognition systems, especially in disturbed viewing conditions. In this study, this information is represented by using a human vision colour appearance ...

The traffic sign recognition system is a support system that can be useful to give notification and warning to drivers. It may be effective for traffic conditions on the current road traffic system. A robust artificial intelligence based traffic sign recognition system can support the driver and significantly reduce driving risk and injury. It performs by recognizing and interpreting various tr...

In this paper, a new algorithm for traffic sign recognition is presented. It is based on a shape detection algorithm that classifies the shape of the content of a sign using the capabilities of a Support Vector Machine (SVM). Basically, the algorithm extracts the shape inside a traffic sign, computes the projection of this shape and classifies it into one of the shapes previously trained with t...

Traffic sign inventories are important to governmental agencies as they facilitate evaluation of traffic sign locations and are beneficial for road and sign maintenance. These inventories can be created (semi-)automatically based on street-level panoramic images. In these images, object detection is employed to detect the signs in each image, followed by a classification stage to retrieve the s...