Abstract
Range imaging based on fast light-sectioning techniques is used to
acquire the three dimensional shape of a steel block with its
embedded flaws. The aim of the paper is the computation of
suitable features for describing the characteristics of
sequentially acquired profiles. The features should discriminate
well between flaws, the intact surface, and pseudo errors caused
by inhomogeneous surface properties such as, e.g., a strongly
changing reflection factor. The orthogonal distance from the
planar curve to its spline approximation serves as a suitable
descriptor. In addition, the multi-scale curvature is useful since
the defects are characterized as local perturbations of a
relatively smooth curve. Since the embedded flaws on the surface
of the steel block are existent in neighboring profiles, a measure
for evaluating the local perturbations with respect to subsequent
profiles is presented. Therefore, a kernel is used for weighting
the neighborhood of a defect. The shape of the kernel might be
Gaussian, however, a special kernel was developed for emphasizing
a preference direction of the flaws.
