20 Aug 2025

SandSnap Filtering Techniques

Abstract: The aim of this Coastal and Hydraulics Laboratory Special Report is to elucidate the new SandSnap image filters. These SandSnap filters distinguish between high-quality and poor-quality images and enhance accuracy in high-quality images. To achieve this goal, a dataset of 5,000 photos was created and curated for this endeavor. Images were collected that had varying levels of focus, sedimentological conditions, foreign objects present, distances from the sediment bed, coin types, and geographic locations. This dataset was used to train multiple quality control check models and uncover beneficial correlations. Additionally, an existing dataset of high-quality images was analyzed using various filtering techniques to highlight key features, leading to higher-accuracy scores. Using the findings from both the high-quality and poor-quality datasets, SandSnap was updated to increase usability and efficiently identify images that may lead to poor results. This ensures that user results can be calculated in less than a minute, emphasizing the commitment to maintaining a fast and responsive model.