scholarly journals Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2093 ◽  
Author(s):  
Safat B. Wali ◽  
Majid A. Abdullah ◽  
Mahammad A. Hannan ◽  
Aini Hussain ◽  
Salina A. Samad ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Sign ◽  
Current Trends ◽  
Sign Detection ◽  
Comprehensive Survey ◽  
Future Vision ◽  
Traffic Sign Detection ◽  
Detection And Recognition

The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system.

scholarly journals A Survey on Traffic Sign Detection Techniques Using Text Mining

2019 ◽  
Vol 8 (S1) ◽  
pp. 21-24
Author(s):  
S. Murugan ◽  
R. Karthika
Keyword(s):  
Recognition System ◽  
Research Area ◽  
Video Data ◽  
Traffic Sign ◽  
Detection Techniques ◽  
Current Trends ◽  
Sign Detection ◽  
Comprehensive Survey ◽  
Traffic Sign Detection ◽  
Detection And Recognition

Traffic Sign Detection and Recognition (TSDR) technique is a critical step for ensuring vehicle safety. This paper provides a comprehensive survey on traffic sign detection and recognition system based on image and video data. The main focus is to present the current trends and challenges in the field of developing an efficient TSDR system. The ultimate aim of this survey is to analyze the various techniques for detecting traffic signs in real time applications. Image processing is a prominent research area, where multiple technologies are associated to convert an image into digital form and perform some functions on it, in order to get an enhanced image or to extract some useful information from it.

scholarly journals Sistema de Multicamadas para Detecção de Placas Sinalizadoras em Tempo Real

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Byron Leite Dantas Bezerra ◽  
Renan Freitas Leite ◽  
Bruno José Torres Fernandes
Keyword(s):  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Sign ◽  
Advanced Driver Assistance Systems ◽  
Sign Detection ◽  
Assistance Systems ◽  
Traffic Sign Detection

O desenvolvimento de sistemas de assistência ao condutor (ADAS, Advanced Driver Assistance Systems) originou uma demanda de técnicas de detecção de placas sinalizadoras em imagens digitais, que estão se tornando cada vez mais robustas. Porém, essas técnicas necessitam de muito recurso computacional para serem executadas em tempo real (30 quadros por segundo). Neste artigo, é apresentado um sistema de detecção de placas sinalizadoras capturadas por câmeras digitais. O modelo proposto consiste de 2 fases de detecção, com o objetivo de juntar técnicas de busca e extração de características, que utilizam o menor custo computacional possível. O modelo possui uma taxa de acurácia acima de 90% na base de dados GTSDB (German Traffic Sign Detection Benchmark) assim como os melhores modelos do estado da arte, porém possui um menor tempo de resposta. Por fim, o sistema foi testado em um ambiente real, por meio de uma câmera digital.

TRAFFIC SIGN DETECTION BASED ON SIMPLE XOR AND DISCRIMINATIVE FEATURES

2016 ◽  
Vol 78 (6-2) ◽  
Author(s):  
Ahmed Madani ◽  
Rubiyah Yusof
Keyword(s):  
Shape Matching ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Sign ◽  
Sign Detection ◽  
Different Color ◽  
Two Stages ◽  
Exclusive Or ◽  
Testing Speed ◽  
Traffic Sign Detection

Traffic Sign Detection (TSD) is an important application in computer vision. It plays a crucial role in driver assistance systems, and provides drivers with safety and precaution information. In this paper, in addition to detecting Traffic Signs (TSs), the proposed technique also recognizes the shape of the TS. The proposed technique consist of two stages. The first stage is an image segmentation technique that is based on Learning Vector Quantization (LVQ), which divides the image into six different color regions. The second stage is based on discriminative features (area, color, and aspect ratio) and the exclusive OR logical operator (XOR). The output is the location and shape of the TS. The proposed technique is applied on the German Traffic Sign Detection Benchmark (GTSDB), and achieves overall detection and shape matching of around 97% and 100% respectively. The testing speed is around 0.8 seconds per image on a mainstream PC, and the technique is coded using the Matlab toolbox.

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