A method for feature extraction of traffic sign detection and the system for real world scene

Traffic signs are an important feature in providing safety information for drivers about road conditions. Recognition of traffic signs can reduce the burden on drivers remembering signs and improve safety. One solution that can reduce these violations is by building a system that can recognize traffic signs as reminders to motorists. The process applied to traffic sign detection is image processing. Image processing is an image processing and analysis process that involves a lot of visual perception. Traffic signs can be detected and recognized visually by using a camera as a medium for retrieving information from a traffic sign. The layout of different traffic signs can affect the identification process. Several studies related to the detection and recognition of traffic signs have been carried out before, one of the problems that arises is the difficulty in knowing the kinds of traffic signs. This study proposes a combination of region and corner point feature extraction methods. Based on the test results obtained an accuracy value of 76.2%, a precision of 67.3 and a recall value of 78.6.

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Traffic Sign Detection Using a Cascade Method With Fast Feature Extraction and Saliency Test

IEEE Transactions on Intelligent Transportation Systems ◽

10.1109/tits.2017.2682181 ◽

2017 ◽

Vol 18 (12) ◽

pp. 3290-3302 ◽

Cited By ~ 10

Author(s):

Dongdong Wang ◽

Xinwen Hou ◽

Jiawei Xu ◽

Shigang Yue ◽

Cheng-Lin Liu

Keyword(s):

Feature Extraction ◽

Traffic Sign ◽

Sign Detection ◽

Cascade Method ◽

Traffic Sign Detection

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

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190823112357 ◽

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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