This paper describes an automatic road sign recognition system by using matching pursuit (MP) filters. The system consists of two phases. In the detection phase, it finds the relative position of road sign in the original distant image by using a priori knowledge, shape and color information and captures a closer view image. Then it extracts the road sign image from the closer view image by usi...

Detection and recognition of traffic signs is an essential task of regulating the traffic, guiding and warning driver’s pedestrians. In traffic sign detection research are categorized into three groups. The first group of researchers believes that traffic sign detection colors are important information by which traffic signs can be detected and classified. The second group believes that detecti...

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of ...

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 sup...

Road sign recognition is one of the core technologies in Intelligent Transport Systems. In the current study, a robust and real-time method is presented to identify and detect the roads speed signs in road image in different situations. In our proposed method, first, the connected components are created in the main image using the edge detection and mathematical morphology and the location of t...

An Automatic Road Sign Recognition System {A(RS)2} is aimed at detection and recognition of one or more road signs from real-world color images. The authors have already proposed an A(RS)2 able to detect and extract sign regions from real world scenes on the basis of their color and shape features. Classification is then performed on extracted candidate regions using Multi-Layer Perceptron neur...

This paper describes a general framework for the detection and tracking of traffic and road signs from image sequences using only color information. The approach consists of two independent parts. In the first we use a set of Gaussian distributions that model each color for detecting road and traffic signs. In the second part we track the targets detected in the first step over time. Our approa...

Road sign detection and tracking is one of the major tasks in a visual driver-assistance system. This paper describes an approach to detecting and tracking road signs appearing in complex traffic scenes. In the detecting phase, two neural networks are developed to extract color and shape features of traffic signs, respectively, from scenes images. A process characterized by fuzzy-set discipline...

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...