scholarly journals Traffic sign detection and recognition by improving Region of Interest (ROI) division to support driver assistance system

2020 ◽  
Vol 850 ◽  
pp. 012042
Author(s):  
A Suheryadi ◽  
A Sumarudin ◽  
A Puspaningrum ◽  
E Prastyo
Keyword(s):  
Driver Assistance System ◽  
Region Of Interest ◽  
Assistance System ◽  
Driver Assistance ◽  
Traffic Sign ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Detection And Recognition

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 Automatic Traffic Sign Detection Practices: A Review

2020 ◽  
Vol 6 (12) ◽  
pp. 117-124
Author(s):  
Tania Joseph
Keyword(s):  
Real Time ◽  
Region Of Interest ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Safe Navigation ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Detection And Recognition

Traffic sign detection and recognition plays an important part in today’s technology driven world. The purpose of traffic signs is to help drivers as well as pedestrians for safe navigation. The two major phases involved in traffic sign detection and recognition are : identifying the region of interest and proceeding to detect any and all signs that might be present, and further, classifying the detected signs into their respective classes. This paper attempts to review all the existing methods/practices for the detection of signs(real-time).

scholarly journals Automatic Traffic Sign Detection Practices: A Review

2020 ◽  
Vol 6 (12) ◽  
pp. 117-124
Author(s):  
Tania Joseph
Keyword(s):  
Real Time ◽  
Region Of Interest ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Safe Navigation ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Detection And Recognition

Traffic sign detection and recognition plays an important part in today’s technology driven world. The purpose of traffic signs is to help drivers as well as pedestrians for safe navigation. The two major phases involved in traffic sign detection and recognition are : identifying the region of interest and proceeding to detect any and all signs that might be present, and further, classifying the detected signs into their respective classes. This paper attempts to review all the existing methods/practices for the detection of signs(real-time).

The Traffic Sign Detection Algorithm Based on Region of Interest Extraction and Double Filter

2019 ◽  
Vol 13 ◽  
Author(s):  
Dongxian Yu ◽  
Jiatao Kang ◽  
Zaihui Cao ◽  
Neha Jain
Keyword(s):  
Region Of Interest ◽  
Detection Algorithm ◽  
Light Filter ◽  
Support Vector ◽  
Detection Accuracy ◽  
Traffic Light ◽  
Traffic Sign ◽  
Traffic Signs ◽  
Sign Detection ◽  
Traffic Sign Detection

In order to solve the current traffic sign detection technology due to the interference of various complex factors, it is difficult to effectively carry out the correct detection of traffic signs, and the robustness is weak, a traffic sign detection algorithm based on the region of interest extraction and double filter is designed.First, in order to reduce environmental interference, the input image is preprocessed to enhance the main color of each logo.Secondly, in order to improve the extraction ability Of Regions Of Interest, a Region Of Interest (ROI) detector based on Maximally Stable Extremal Regions (MSER) and Wave Equation (WE) was defined, and candidate Regions were selected through the ROI detector.Then, an effective HOG (Histogram of Oriented Gradient) descriptor is introduced as the detection feature of traffic signs, and SVM (Support Vector Machine) is used to classify them into traffic signs or background.Finally, the context-aware filter and the traffic light filter are used to further identify the false traffic signs and improve the detection accuracy.In the GTSDB database, three kinds of traffic signs, which are indicative, prohibited and dangerous, are tested, and the results show that the proposed algorithm has higher detection accuracy and robustness compared with the current traffic sign recognition technology.

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