Traffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which ach...

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, 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...

The timely provision of traffic sign information to drivers is essential for the drivers to respond, to ensure safe driving, and to avoid traffic accidents in a timely manner. We proposed a timely visual recognizability quantitative evaluation method for traffic signs in large-scale transportation environments. To achieve this goal, we first address the concept of a visibility field to reflect ...

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-...

Traffic sign detection is an important research direction in the process of intelligent transportation Internet era, and plays a crucial role ensuring traffic safety. The purpose this to propose traffic-sign-detection algorithm based on selective kernel attention (SK attention), explicit visual center (EVC), YOLOv5 model address problems small targets, incomplete detection, insufficient accurac...

Recently, intelligent transportation systems (ITS) attracts more and attention for its wide applications. Traffic sign detection recognition (TSDR) system is an essential task of ITS. It enhances the safety by informing drivers about current state traffic signs offering valuable information precautions. This paper reviews popular methods (TSD) prevalent in recent literature. The are divided int...

Aiming at solving the problem of missed detection and low accuracy in detecting traffic signs wild, an improved method YOLOv8 is proposed. Firstly, combined with characteristics small target objects actual scene, this paper further adds blur noise operation. Then, asymptotic feature pyramid network (AFPN) introduced to highlight influence key layer features after fusion, simultaneously solve di...