High-resolution characterization of seafloor sediment microtopography is essential for understanding benthic habitat structure, sedimentary processes, and ecological function. However, existing methods typically rely on core-based sampling or specialized 3D imaging systems, both of which are limited by cost, complexity, and scalability. In this study, we present a cost-effective, camera-based framework for quantitative sediment surface analysis using video footage from a drifting monocular underwater camera. The method leverages a zero-shot application of RAFT-Stereo to estimate dense disparity maps from sequential frames without requiring prior training on sediment data. We then extract statistical and morphological roughness features. Through a small-scale case study, we evaluate the method on two distinct sediment types, Sand and Shell-Hash, and demonstrate that the extracted features effectively capture surface complexity. This framework offers a scalable, non-invasive solution for retrospective and in-situ sediment analysis in marine monitoring. The code is publicly available at: https://github.com/shahrokh1106/sediment-microtopography-monocamera