An Image Recognition Application Method for Vertical Movement of Vehicles

In ITS, image processing technology is applied to a wide variety of areas such as visual-based intelligent vehicle navigation, visual-based traffic monitoring and visual-based traffic management. In the identification system of the vehicle body characteristics, most of the recognition is the license plate and the car emblem, etc. This paper proposes an image recognition application method for the vertical motion of the car while driving, mainly including vertical height detection and vertical displacement velocity acceleration recognition. The edge detection model of the image object is established by using the gray image to obtain the car motion segmentation image. At the same time, an image length and actual length coordinate conversion model is established, which can calculate an arbitrary actual length of the image object. In this paper, the Yuejin Shangjun X500 van is selected as the test vehicle. Using camera capture the video data and the height of the vehicle is recognized for each frame. The height is compared with the actual length. The absolute error can be controlled within 40mm, and the minimum relative error can reach 1.23%. The data is processed to obtain the vertical motion curves, and the root mean square (RMS) value of the weighted acceleration of the vertical motion can be calculated to judge the comfort of the human senses, which can also be used for car ride comfort evaluation. At the same time, the recognition height can judge whether the vehicle is over-height in time. This method can be used for monitoring and evaluating vehicles, which is of great significance for traffic monitoring and management.