Nowadays, drivers may ignore traffic signs on the road or because of hazardous weather (fog, rain, etc.) in order to concentrate on driving, which could be dangerous for both vehicles and pedestrians. Without causing drivers to lose concentration while driving, this software solution would assist in detecting and identifying traffic signs. In driver assistance systems that relieve the driver of some tasks as well as in intelligent autonomous vehicles, traffic sign recognition is crucial. To decrease traffic accidents and allow for greater driving freedom, a model that can automatically detect and recognize traffic signs on traffic sign has been required. This demand is satisfied by traffic sign recognition systems. Application for the detection and recognition of traffic signs is part of this project. Some image processing techniques are employed in this study to find and identify traffic signs. Traffic sign detection and classification are the two components of this architecture. This essay suggests many techniques for spotting and identifying traffic sign boards. For the identification and indication of traffic signs, a variety of techniques are used, including color segmentation and RGB to HIS models. Recognition includes things like form context and HOG features. The number of automobiles in use today is rising quickly. Traffic signs and the number of ways have both increased concurrently. Due to the proliferation in traffic signs, drivers are obliged to get familiar with all of them and to pay close attention to them while driving.
Enhancing Road Safety: Automated Traffic Sign Detection and Recognition Using Image Processing Techniques
Algorithms for Intelligent Systems
International Conference on Deep Learning and Visual Artificial Intelligence ; 2024 ; Bikaner, India March 15, 2024 - March 16, 2024
2024-09-18
10 pages
Article/Chapter (Book)
Electronic Resource
English
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