Abstract
Digital image correlation (DIC) has emerged as a popular full-field surface profiling technique for analyzing both in-plane and out-of-plane dynamic structures. However, conventional DIC-based surface 3D profilometry often yields erroneous contours along surface edges. Boundary edge detection remains one of the key issues in DIC because a discontinuous surface edge cannot be detected due to optical diffraction and height ambiguity. To resolve the ambiguity of edge measurement in optical surface profilometry, this study develops a novel edge detection approach that incorporates a new algorithm using both the boundary subset and corner subset for accurate edge reconstruction. A pre-calibrated gauge block and a circle target were reconstructed to prove the feasibility of the proposed approach. Experiments on industrial objects with various surface reflective characteristics were also conducted. The results showed that the developed method achieved a 15-fold improvement in detection accuracy, with measurement error controlled within 1%.
Highlights
Optical surface profilometry has a broad range of applications, especially for the measurement of critical dimensions and the process automation of industrial workpieces
Three-dimensional surface profilometry is a crucial technology for the quality inspection of various manufacturing processes
Thereimage exists acan discontinuous surfacebecause edge, subset pattern matching between the template theWhen measured no longer succeed the subset random-speckle pattern, reference template and the measured image can no longer succeed because the subset under such circumstances, is projected on both sides of the detected surface jump with a random-speckle pattern, underthe such circumstances, projected on both of the detected step-height difference between projected images. is 3 shows howsides a continuous surfacesurface edge jump with a step-height difference between the projected images
Summary
Optical surface profilometry has a broad range of applications, especially for the measurement of critical dimensions and the process automation of industrial workpieces. To achieve single-exposure full-field surface profilometry, the 3D DIC-based random-speckle methodology projects random laser speckles on the tested surface and evaluates absolute depth through correlating the captured image with pre-calibrated reference images [2,3]. In such a process, a set of image blocks with unique. 3D surface boundary edge detection remains a major challenge for DIC-based surface been developed, nor has the feasibility of current measurement approaches in industrial applications been carefully evaluated. 3 ofwas developed, and its applicability to measuring industrial objects was assessed
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