A Method to Search for Color Segmentation Threshold in Traffic Sign Detection

2009 ◽  
Author(s):  
Ling Luo ◽  
Xiying Li
Keyword(s):  
Color Segmentation ◽  
Traffic Sign ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Segmentation Threshold

scholarly journals Traffic Sign Detection based on Color Segmentation of Obscure Image Candidates: A Comprehensive Study

2018 ◽  
Vol 10 (6) ◽  
pp. 35-46 ◽  
Author(s):  
Dip Nandi ◽  
◽  
A.F.M. Saifuddin Saif ◽  
Prottoy Paul ◽  
Kazi Md. Zubair ◽  
...  
Keyword(s):  
Color Segmentation ◽  
Traffic Sign ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Comprehensive Study

scholarly journals A Access Traffic Sign Detection Tracking and Recognition System for Video Frames using KNN Algorithms

2019 ◽  
Vol 8 (11S) ◽  
pp. 56-61
Keyword(s):  
Autonomous Vehicles ◽  
Recognition System ◽  
Color Segmentation ◽  
Physical Sign ◽  
Traffic Sign ◽  
Sign Recognition ◽  
Video Frames ◽  
Sign Detection ◽  
Traffic Sign Detection ◽  
Tracking And Recognition

Video-based traffic sign detectiontracking and recognition plays an important role in driving support system as well as in intelligent autonomous vehicles. This framework includes three parts like traffic sign detecting, target tracking and sign recognition. This paper contributes different methods for detecting and recognizing of traffic sign, so that drivers can be easily identify the type of signal in road sides. In this approach different methods like color segmentation and scale based intraframe fusion technics is proposed which includes the spatial-temperol constraints in videos, by fusing the different casings that have a place with an equivalent physical sign along to induce higher exactness.

TRAFFIC SIGN DETECTION AND RECOGNITION: REVIEW AND ANALYSIS

2015 ◽  
Vol 77 (20) ◽  
Author(s):  
Nursabillilah Mohd Ali ◽  
Mohd Safirin Karis ◽  
Amar Faiz Zainal Abidin ◽  
Bahzifadhli Bakri ◽  
Ezreen Farina Shair ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Color Segmentation ◽  
Traffic Sign ◽  
Driving Experience ◽  
Adverse Weather ◽  
Sign Detection ◽  
Computational Difficulty ◽  
User Friendly ◽  
Traffic Sign Detection ◽  
Detection And Recognition

Over the years, traffic sign detection and recognition systems gives extra value to driver assistance when driving, leading to more user-friendly driving experience and much improved safety for passengers. As part of Advanced Driving Systems (ADAS) one can be benefitted by using this system especially with driving incapacities by alerting and aid them about the existence of traffic signs to minimized unwanted circumstances during driving such as fatigue, poor sight and adverse weather conditions. Though a various number of traffic sign detection systems have been revised in literature; the need of design with a robust algorithm still remains open for further research. This paper purposes to design a system capable of performing traffic sign detection while considering variations of challenges such as color illumination, computational difficulty and functional constraints existed. Traffic sign detection is divided into three main parts namely; Pre-processing, Color segmentation and Thresholding. The color segmentation method is vital as it presents a detailed investigation of vision based color spaces in this case RGB, HSV and CMYK considering varying illumination conditions under different environments. This paper further highlights possible improvements to the proposed approaches for traffic sign detection.

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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