Python Image Processing - Traffic Sign Recognition Method Under Complex Conditions - ClickMyProject
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Traffic signs play an important
Traffic signs play an important role for Advanced Driver Assistance Systems (ADAS) as well as for autonomous driving vehicles. Most of the works done focus on recognizing symbol based signs leaving apart important information provided by other type of signs like complementary panels or text based signs. In this paper, we include detection and classification of both symbol and text based signs focusing on the most common ones found in European urban environments. Environment awareness technology is one of the most critical technologies for autonomous vehicles, and traffic sign recognition is an important branch of environment awareness system, which has important research significance for ensuring traffic safety. The system consists of three stages, traffic sign detection and classification. To achieve this goal, we evaluated the performance of two common pretrained deep learning models (DCNN and ResNet50). Then, we can implement the YOLO v8 for detecting the bounding box and compared their accuracy levels when detecting the traffic sign. Finally, the system can estimate some performance metrics such as accuracy and error rate for both algorithms and compare the algorithms based on accuracy in the form of graph. Experimental results on German environments show that our proposed system is capable of detecting all categories of traffic signs while at the same time recognizing them with high accuracy achieving comparable performance with the state of the art.
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ماه قبل
در تاریخ 1403/05/14 منتشر شده
است.
11
بـار بازدید شده