Non-uniform surface sampling techniques for three-dimensional object inspection

While the uniform sampling method is quite popular for point-wise measurement of manufactured parts, we present three novel sampling strategies that emphasize 3D non-uniform inspection capability. They are direct and indirect adaptive sampling and local adjustment sampling. The adaptive sampling strategy is based on a recursive surface subdivision process that applies two different approaches. One uses the direct triangular patch subdivision while the other uses the indirect sectional adaptive approach. The direct adaptive sampling approach can distribute points more closely around edges, corners, and vertices as found on the class of machined products. The indirect adaptive sampling techniques extend optimum 2D sampling methods to 3D applications. The modified 2D adaptive sampling techniques are used sequentially twice; first, the critical cross sections are optimally selected, and then each section is optimally sampled to develop an accurate geometric description using a small number of sampling points. Beyond the practical application value of a technique to inspect curved surface objects, this kind of technique is also of value in understanding the principle of optimum sampling in a 3D sense. The local adjustment sampling strategy uses a set of predefined starting points and then finds the local optimum position of each nodal point. This method approximates the object by moving the points toward object edges and corners. The predefined starting points sets include uniform and non-uniform sampling distribution generated by the direct adaptive sampling approach. The results show that the initial point sets, when preprocessed by the adaptive sampling using triangular patches, are moved the shortest distance to edges and corners for global optimum approximation, again showing this method's superiority. The performance comparisons of applying uniform sampling and adaptive sampling are made based on the MSE (mean square error) value between the real object surfaces and their approximating surfaces. The adaptive sampling methods exhibit better performance than the uniform sampling methods in reducing the MSE values with fewer sample points. In addition to the performance advantage over uniform sampling, the non- uniform sampling techniques we propose also proved to be integratable with view planning for the inspection of products by different manufacturing processes. (c) 2008 Society of Photo- Optical Instrumentation Engineers.