The use of cold-formed steel (CFS) members in construction have increased significantly due to the recent advances in cold-formed steel research and the developed design guidelines. CFS construction provides affordable, light, efficient, and resilient building systems. CFS members are obtained by forming thin steel sheets into several different cross-sections. Due to transportation, installation, and even production, geometrical imperfections may occur on the thin steel sheets that form the CFS members. These geometrical imperfections affect the predicted physical response of CFS members. Thus, in order to efficiently compute the physical response of a CFS member, it is necessary to determine the geometric imperfections and investigate their effect on member behavior. In this paper, a low-cost methodology for extracting the 3D surface data of CFS members from 2D images that could be later used for geometric imperfection extraction is proposed.