Abstract: Apparatus (10) for determining the leading edge (E) of an airfoil (A) includes a first light source (S1) illuminating a portion of the airfoil including its leading edge and a first camera (M1) acquiring an image of the illuminated portion of the airfoil. A second light source (S2), spaced apart from the first light source, also illuminates a portion of the airfoil including its leading edge. A second camera (M2) acquires an image of the portion of the airfoil illuminated by the second light source. The location (N2) of the second light source and the first camera are coincident in space as are the location (N1) of the first light source and the second camera. An image processor (P) processes the respective images obtained from the two cameras to locate the leading edge of the object. In doing so, the processor utilizes similarities in illumination of the airfoil by the respective light sources and occlusion boundaries of the respective illuminated portions of the airfoil.

Abstract: A method for determining the axis of rotation (AR) of an object (12) mounted to a rotary stage or platform (10) in a gauge measurement system by estimating a transformation (&dgr;) between multiple views or measurements of the object (12) obtained at different poses.

Abstract: A method for use with a non-contact range finding and measurement system for generating a template guide representative of the surface of a observed object, and for utilizing the template guide to improve laser stripe signal to noise ratios and to compensate for corrupted regions in images of the observed object to improve measurement accuracy.

Abstract: A method for generating, in a non-contact range finding and measurement system, a template structure representative of the surface of an observed object, and for utilizing the template structure to synthesize data points in corrupted regions of an image of the object.

Abstract: A base pair of minutia is selected in the latent fingerprint under consideration and each tenprint or reference fingerprint. For each selected base pair, those sets of minutia pairs are selected which satisfy apriori constraints including angle, distance and ridge counts, to generate a first set of minutia which support the fingerprint correspondence. A second set of the supporting minutia pairs is generated from the first set, which doesn't contain pairs which are inconsistent with the base pair/bias angle. A third set is established using "dynamic programming" to determine the largest topologically self-consistent subset of the second set. The minutia pairings are counted in the third set, to thereby establish a merit of the base pair. For each of the minutia of the latent fingerprint, a correspondence group is generated, of a predetermined number of minutia of the tenprint which have the greatest merit.