Introduction Plastic running tracks are widely used in sports fields due to their excellent performance in terms of shock absorption, slip resistance, and durability. However, it is a challenging task to accurately mark the running tracks on the plastic surface. The traditional marking methods such as painting and tape laying have several drawbacks, including low accuracy, high cost, and frequent maintenance. To overcome these issues, a plastic running track marking algorithm based on computer vision has been proposed. In this article, we will discuss the details and benefits of this algorithm. Background Plastic running tracks are made of synthetic materials such as polyurethane, which provides excellent elasticity and durability. However, marking the running tracks on the plastic surface is a challenging task. The traditional marking methods such as painting and tape laying have several drawbacks. Firstly, the accuracy of the markings is low, which affects the performance of athletes. Secondly, the cost of these methods is high, and frequent maintenance is required. To overcome these issues, a plastic running track marking algorithm based on computer vision has been proposed. Algorithm The plastic running track marking algorithm is based on computer vision and image processing techniques. The algorithm uses a camera to capture images of the running track surface and then processes these images to mark the running tracks accurately. The algorithm consists of the following steps: Step 1: Image acquisition The first step is to acquire images of the running track surface using a camera. The camera should be positioned at a suitable height and angle to capture the entire running track surface. Step 2: Image processing The acquired images are then processed to extract the running track boundaries. The image processing techniques used in this step include edge detection, thresholding, and morphological operations. Step 3: Marking the running track Once the running track boundaries are extracted, the algorithm marks the running track by drawing lines on the plastic surface. The marking process is done using a laser or a robot arm equipped with a marking tool. Benefits The plastic running track marking algorithm has several benefits over traditional marking methods. Firstly, the accuracy of the markings is high, which ensures that athletes can perform at their best. Secondly, the cost of the algorithm is low compared to traditional methods, and frequent maintenance is not required. Thirdly, the algorithm can be easily customized to mark different types of running tracks, including oval, straight, and curved tracks. Conclusion In conclusion, the plastic running track marking algorithm based on computer vision is a promising solution to accurately mark running tracks on plastic surfaces. The algorithm uses image processing techniques to extract the running track boundaries and mark the running track accurately. The benefits of this algorithm include high accuracy, low cost, and easy customization. With the increasing demand for plastic running tracks, this algorithm has the potential to revolutionize the way running tracks are marked.