Over-limit transportation is the leading cause of highway pavement diseases and traffic accidents. The Ministry of Transport of China has determined the weight limit for different trucks entering the highway based on the number of truck axles and the coupling method. However, because determining the truck weight limit is more complicated, the current work is mainly done manually by the toll station staff at the expressway entrance, and the recognition speed is slow Cand the recognition result is inaccurate. In response to this problem, we first analyzed and established the relationship between the number of axles and the position distribution, and the truck weight limit. Based on the above, we developed a circle detection method with an improved Hough and CURE algorithm as the core to identify truck wheel axles. We collect 100 test images at the expressway entrance and use 50 of them to perform detection experiments to determine the radius step, angle step, and the maximum and minimum circle values during the detection process. After using the entire data set, comparing the hough algorithm, the improved Hough algorithm, and our proposed method, the results show that our proposed method has higher accuracy and efficiency.
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