Quality Control in Automated Manufacturing Processes – Combined Features for Image Processing

Abstract

In production processes the use of image processing systems is widespread. Hardware solutions and cameras respectively are available for nearly every application. One important challenge of image processing systems is the development and selection of appropriate algorithms and software solutions in order to realise ambitious quality control for production processes. This article characterises the development of innovative software by combining features for an automatic defect classification on product surfaces. The artificial intelligent method Support Vector Machine (SVM) is used to execute the classification task according to the combined features. This software is one crucial element for the automation of a manually operated production process.