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...

This paper presents a survey on the detection and recognition of traffic signs which has a number of important application areas that include advanced driver assistance systems, road surveying and autonomous vehicles. This has been thoroughly studied for a long time. But still it remains a challenging problem in computer vision due to the different types and the huge variability of informations...

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-...

O the last several decades, the use of symbol signs on North American highways has increased significantly. Research has shown that older drivers have difficulty in detecting, reading and understanding symbolic traffic signs. Previous research on their comprehension indicates that some symbols are clearly understood by 90 percent or more of the drivers, while others are understood by fewer than...

Real-time road sign recognition has been of great interest for many years. This problem is often addressed in a two-stage procedure involving detection and classification. In this paper a novel approach to sign classification is proposed. In many previous studies focus was put on deriving a possibly most discriminative set of features from a large amount of training data using global selection ...

In this paper, a novel method is proposed for the Traffic Sign Recognition (TSR) using the Principle Component Analysis (PCA) and the Multi-Layer Perceptron (MLPs) network. In particular to the proposed morphological classification method, the candidate signs are individually detected from two chrome components of the YCbCr space and then classified into three shape classes: circle, square, and...

Motion blur appearing in traffic sign images may lead to poor recognition results, and therefore it is of great significance to study how to deblur the images. In this paper, a novel method for deblurring traffic sign is proposed based on exemplars and several related approaches are also made. First, an exemplar dataset construction method is proposed based on multiple-size partition strategy t...

The intelligent road is an important component of the vehicle infrastructure cooperative system, latest development transportation systems. As advanced sensor, Light Detection and Ranging (LiDAR) has gradually been used to collect high-resolution micro-traffic data on roadside roads. Furthermore, a fusion multiple LiDARs become current hot spot extend collection range improve detection accuracy...