We present a system for the large-scale automatic traffic signs recognition and mapping and experimentally justify design choices made for different components of the system. Our system works with more than 140 different classes of traffic signs and does not require labor-intensive labelling of a large amount of training data due to the training on synthetically generated images. We evaluated o...

This paper proposes a method for constructing an accurate traffic sign detector by retrospectively obtaining training samples from in-vehicle camera image sequences. To detect distant traffic signs from in-vehicle camera images, training samples of distant traffic signs are needed. However, since their sizes are too small, it is difficult to obtain them either automatically or manually. When dr...

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...

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. In real time environment, vehicles move at high speed on roads. For the vehicle intelligent system it becomes essential to detect, process and recognize the traffic sign which is coming in front of vehicle with high relative velocity, at the right time, so that the driver would be able to pro-act ...

Traffic signs provide drivers important information for safety and efficient navigation. Automatic detection and recognition of traffic signs inevitably become more popular. In this paper, an efficient algorithm/platform is presented to achieve automatic alert traffic signs detection and recognition. Histogram of Gradient (HOG) is adapted to extract features and an over-complete set of 1680 fea...

success of effective communication of traffic sign messages to road users may not only relate to the user characteristics but also the signs themselves. The purpose of this experiment was to examine the cognitive design features of 120 Mainland China traffic signs. The features included familiarity, concreteness, simplicity, meaningfulness, and semantic closeness. Forty-one Hong Kong Chinese en...

In this paper, we propose a new approach to detect salient traffic signs, which is based on visual saliency and auto-generated strokes for image segmentation. The proposed algorithm deals with two tasks on detecting traffic signs: auto-location and auto extraction. Firstly, inspired by recent work of visual saliency detection, we obtain the location of traffic signs in a natural image by multi-...

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 ...

1 Traffic signs are an integral element of any transportation network; however, keeping records of 2 those signs and their conditions is a tedious process, which is both time consuming and labour 3 intensive. As a result, many agencies around the world have been working towards automating the 4 process of sign collection. One form of automation is using remote sensing techniques to extract 5 tr...

Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, we present a Chinese traffic sign detection algorithm base...