A Low-Cost Portable Automatic System for Snow Surface Roughness Measurements Based on Digital Photography

In this paper, we present a system for snow roughness measurement. The system is made up of digital camera and a black Forex panel. The whole system has been designed for being low cost and portable; and will be distributed as an open-source Python software. The system is based on the coregistration of the photos taken at the panel on the field with a reference scaled image with pixel size of 0.05 mm. In detail, the coregistration process is done by computing the homography, whose parameters are estimated exploiting automatic key-points matching. Among all methods for keypoints extraction, we used the scale invariant feature transform (SIFT) because of its robustness and recognized efficiency. After key-points extraction, the matching has been performed using a brute force matching (BFM) approach. The proposed system has been tested under different conditions, showing to be an effective and easy approach to snow surface roughness measurement, as well as robust.