A General Methodology for Shape Defect Detection 1 Shape Defect Detection Problem

In the framework of the European technological research project SQUASH 2], a general methodology is presented for shape measurement and defect detection of industrially produced objects using their characteristic 2D projections. The method is applied to the visual inspection and dimensional measurement of ferrite cores. In industrial shape defect detection, two types of measurements can be distinguished: (a) Direct, or absolute, measurements, when a dimension or another quantity to be measured are speciied with respect to particular shape features (corners, etc.) that are easy to identify and locate. An example is measuring the distance between centroids of two holes. (b) Relative measurements, which are speciied with respect to a reference shape. Most of direct measurements are straightforward, as they usually have precise mathematical deenitions in terms of images. Such computational deenitions are relatively easy to translate into a computer algorithm. Relative measurements are much more challenging, as the deenitions are, in fact, implicit. Here, one compares a measured shape to a reference (ideal) shape. For shift-and rotation-invariant comparison, optimal reference position and orientation (pose) of the measured shape is to be found, which requires invariant matching of the two shapes. The pitfall of matching for defect detection is that no reference pose (e.g., baseline) can be speciied a priori because defects may deteriorate any part of the shape. It is a typicaìchicken-and-egg' problem. What parts of a measured