Computed-tomography-based precision inspection and shape extraction using facet model

We apply the facet model to extract edge and surface information from compu ted tomography (CT) images for precision inspection and shape extraction. F irst we explore the application of the facet model in a three-dimensional ( 3-D) filter design. A 3-D directional-derivative-based surface detector is developed to extract surface points from the CT images. Subpixel accuracy i s achieved by locating the zeros of the 3-D second directional derivative a long the estimated gradient direction. Then we develop a precision inspecti on system to take turbine blade wall width measurements from CT images and compare them to the corresponding optical measurements. Least mean squares (LMS) methods are used to enhance prediction accuracy with the adaptive pro perty of increasing accuracy when additional verifiable data are available. The system accuracy is within 3 mil. Unverified measurements are adjusted based on the verified measurements, and experiments show increasing accurac y of the adjusted measurements as additional verified measurements are avai lable. Also, quantitative analysis of a trapezoid-shaped workpiece is perfo rmed. The results indicate that the CT system performance is affected by th e structure and size of a workpiece. We also present an algorithm to extrac t 3-D shapes from detected surface points interactively and use them for vi sual inspection, (C) 2000 Society of Photo-Optical Instrumentation Engineer s. [S0091-3286(00)01401-X].