The edge and surface inspection is one of the most important and most challenging tasks in quality assessment in industrial production. Typical defects are cracks, inclusions, pores, surface flakings, partial or complete tears of material surface and s.o. These defects can occur through defective source material or through extreme strain during machining process. Detection of defects on a materialc surface can be complicated due to extremely varying degrees of material brightness or due to shadow areas, caused by the folding of the surface. Furthermore, impurities or surface discolourations can lead to artefacts that can be detected as pseudo-defects. The brightness conditions on the edge of material defects are interpreted as a Gauss distribution of a radiation and used for a physical model. Basing on this model, an essentially new set of adaptive edge-based algorithms was developed. Using these methods, different types of defects can be detected, without the measurements being dependent on local or global brightness conditions of the image taken. The new adaptive edge-based algorithms allow a defect detection on different materials, like metal, ceramics, plastics and stone. These methods make it possible to explicitly detect all kinds of different defects independently of their size, form and position and of the surface to be inspected. The adaptive edge-based methods provide a very wide spectrum of applications.

The human ability to recognize objects on various backgrounds is amazing. Many times, industrial image processing tried to imitate this ability by its own techniques. This book discusses the recognition of defects on free-form edges and - homogeneous surfaces. My many years of experience has shown that such a task can be solved e?ciently only under particular conditions. Inevitably, the following questions must be answered: How did the defect come about? How and why is a person able to recognize a speci?c defect? In short, one needs an analysis of the process of defect creation as well as an analysis of its detection. As soon as the principle of these processes is understood, the processes can be described mathematically on the basis of an appropriate physical model and can then be captured in an algorithm for defect detection. This approach can be described as "image processing from a physicist's perspective". I have successfully used this approach in the development of several industrial image processingsystemsandimprovedupontheminthecourseoftime.Iwouldlike to present the achieved results in a hands-on book on the basis of edge-based algorithms for defect detection on edges and surfaces. I would like to thank all who have supported me in writing this book.