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Unmanned, automation is the development direction of modern industry, in the application scenarios of automated vehicle scales, aiming at the existing vehicle shaft type detection methods, the use of equipment needs to damage the road surface, and the problems of installation and maintenance are inconvenient, as the HOG operator has better ability to obtain tire edge and describe local shape, and the MB-LBP operator has strong ability to resist light and is robust to small-scale displacement. And a new tire detection algorithm based on HOG and MB-LBP feature fusion was designed for tire detection. Secondly, a wheelbase measurement method based on image calibration and target detection was designed based on the principle of camera imaging and image ranging. Subsequently, determine the axle shape of the vehicle based on the tire and wheelbase test results. Finally, relevant experiments are designed to verify the effectiveness and accuracy performance of the proposed algorithm.The success rate of shaft type detection is 97.65%.