Direct surface parameter estimation using structured light: A predictor-corrector based approach

The projection of structured light is a technique frequently used in computer vision to determine the surface structure of scene objects. In this work, higher level features are extracted from the images and used for a direct estimation of second-order object surface model parameters. In particular, a class of cylinders is emphasized, due to an underlying application involving the inspection of stored drums containing mixed waste. The strategy is based upon a predictor-corrector approach which utilizes an initial estimate for the surface parameters, followed by iterative parameter refinement. A predicted passive image is generated using the current surface parameter estimates and significant features are extracted and compared with those in the true passive image. The estimated surface parameters are corrected based upon feature disparities. In computer simulations and laboratory experiments using real image data, the algorithm was found to converge quickly and to yield accurate results.