Vehicle Detection Technology Based on HSV Color Model and Edge Detection

Abstract

The logistics industry has entered a comprehensive and rapid development stage. The prerequisite for the normal operation of logistics enterprises lies in the improvement of transportation efficiency and the enhancement of the management of queuing areas such as gate posts, loading and unloading points. It is also an important way to reduce costs, improve profits and enhance the competitiveness of enterprises. Aiming at the problems of traditional traffic flow detection algorithm, such as single feature extraction, vulnerable to weather, poor robustness and easy to be blocked by vehicles, this paper proposes a joint detection algorithm. The detection algorithm is a joint scheme of edge detection and HSV color model, and adopts Gaussian filtering to calculate traffic flow based on morphology and image segmentation. The experimental results show that the combined algorithm can not only alleviate the impact of the light and shadow environment in the daytime, improve the robustness of the system, and make the detection more accurate, but also reduce the counting problem caused by the congestion between vehicles, which is helpful to alleviate the road congestion and ensure the transportation efficiency and safety.