Traffic Sign Recognition (TSR) is used to regulate traffic signs, warn a driver, and command or prohibit certain actions. Fast real-time and robust automatic traffic sign detection and recognition can support and disburden the driver and significantly increase driving safety and comfort. Automatic recognition of traffic signs is also important for an automated intelligent driving vehicle or for...

In this study, a numerical computational fluid dynamics study is conducted in order to predict the aerodynamic forces on the NP car. The turbulent air flow around the car is modeled using the realizable k-ε model. First, results are validated against those presented for the Ahmed’s body. Next, the fluid flow around the car is simulated for different car speeds ( to mph) and fl...

Sophisticated digital map is an essential resource for intelligent vehicles to localize and retrieve environment information. However, the open map resource do not contain enough information for decision making during autonomous driving. Although comprehensive commercial map can provide precise map knowledge, the data format is not in a machine-readable format. Therefore, we retrieve useful kno...

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 detecting phase, two neural networks are developed to extract color and shape features of traffic signs, respectively, from the input scene images. Traffic signs are then located in the...

In this paper we present an approach to detect traffic guidance signs and recognise the structure of junction information on them. The detection algorithm is based on using differently exposed images. These images are combined into one using tone mapping technique in order to minimize effects of bad environment conditions and low dynamic range of CCDcameras. This technique allows robust sign de...

This paper purposed a Traffic Sign Recognition (TSR) system which can automatically detect and classified the traffic signs in traffic scene images acquired from a moving car. First it uses color based segmentation and then further refines the segments using two shape detection based techniques. A color description technique is used to extract the sign information from the segmented part which ...

The real-time road traffic sign recognition focused on the application of computer vision techniques in automatic detection and classification of video images of traffic signs placed on roadways acquired from moving vehicles. In this work, we present results of an attempt to locating traffic signs placed on local roadways based on image processing techniques. The developed algorithm is based on...

Night vision systems in vehicles are a new emerging technology. A crucial problem in active (laser-based) systems is distortion of images by saturation and blooming due to strong retroreflections from road signs. We quantify this phenomenon. We measure the Mueller matrices and the polarization state of the reflected light from three different types of road sign commonly used. Measurements of th...

This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support...

In this paper we present an approach to the detection and extraction of text in road sign panels. Text strings, indicators and signs extraction is efficiently performed so OCR algorithms can recognize different characters that may be present on the traffic plane. In a first step, basic color segmentation and shape classification is done for the purpose of detecting possible rectangular planes. ...