Visual Inspection Systems

  • Edwin Lughofer
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 266)


Following the previous chapter, the first part of this chapter again deals with quality control and fault detection aspects. However, instead of supervising raw process data (measurement signals), here we deal with two-dimensional visual context information in form of images. In particular, in Section 9.1 we demonstrate how images showing the surface of production items will be analyzed if they show any untypical occurrences which may indicate faults on single items, usually caused by failures in the production systems. The second part of this chapter deals with visual context information in form of textures, which can be seen as special types of images containing repeating patterns over their complete range. Human perception modelling for visual textures will be the core aspect of the second part. This means that models will be built for the purpose to associate human perception and emotions with given visual textures. These association models require a visual texture as input and are able to respond to a certain emotion the input texture may trigger for customers.


Inspection System Mean Absolute Error Aesthetic Property Visual Texture Aggregate Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Edwin Lughofer

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