AI Summary & Key Takeaways
AI InsightThis study provides an improvement in this area due to the fact that studies on the literature related to the determination of the level crossing and foreign objects in the level crossing based image processing are not enough.
📌 3 Key Takeaways
Abstract
Level crossings are an important part of rail and road transportation and are areas where serious accidents occur in. Most of the accidents in railway transportation are happening in the level crossings. In this paper, a vision-based method is proposed for the prevention of these accidents in the level crossing. With this method, which is based on image processing, the condition monitoring of the level crossing is performed. The obstacles in the level crossing are detected and the estimated distance of these obstacles to the camera is calculated in the proposed method. In order to detect the obstacles in the level crossing, the level crossing in the railway image is determined first. YCbCr color transformation, edge extraction, filtering and Hough transformation have been applied to the image in the detection of the level crossing. The detected level crossing area has been labeled as the grade crossing in the image. It has been checked whether or not it has obstacles at the level crossing. HSV color transformation, image difference extraction, gradient calculation, filtering, detection of connected components and feature extraction have been applied to object detection. A single camera has been used in the proposed method to calculate the distance between the detected foreign object and the camera. The number of pixels covered by the object in the image is taken into account in calculating the distance between the object and the camera. The distance of objects at different distances from the camera is calculated in proportion to the number of pixels in the reference image. This study provides an improvement in this area due to the fact that studies on the literature related to the determination of the level crossing and foreign objects in the level crossing based image processing are not enough.