Snow detection model using Mask R-CNN with road monitoring camera images

Abstract

This study created training data by manually classifying road conditions into "snow-covered" and "non- snow-covered" categories using images from road monitoring cameras installed on major roads, serving as a support tool for road administrators and residents to quickly check road surface snow conditions. Additionally, an AI model for automatic road surface snow condition detection was developed and tested using 400 images taken during both day and night. As a result, the accuracy rate was approximately 85% or higher.