Defect detection

The major components of a machine vision system are image acquisition and image processing. The complexity of image acquisition is based on the huge number of degrees of freedom. This article introduced an extension of a sensor simulation tool which enables a user to simulate the current sensor positions and field of views. The results are registered point clouds from different sensor positions merged to a final object point cloud. Now it is possible to evaluate image processing techniques based on the simulated 3D data, without explicit results from the real sensor behaviour. The benefits of the tool were demonstrated in a real micro cold forming scenario. Future work focuses on additional sensor noise models. Adding these models results in a more realistic sensor simulation framework.

Surface inspection and defect detection during manufacturing is a fundamental task for industrial image processing. Based on reliable and accurate defect detection systems changing process behaviour, like blunt tools, can be detected. In many areas like Si-wafer production, optical quality control is still state of the art. Nevertheless, in many cases a completely new and specialised image processing technique will be developed for every new problem. This contribution demonstrates a method for a general image processing technique for industrial surface inspection which is not limited to a specific hardware or defect type. The system is part of the Collaborative Research Center (CRC) 747 “Micro Cold Forming” and will be evaluated in a real cold forming process.