Real-time image processing

ClassIcam: Entwicklung von Klassifikationsmodellen für intelligente Netzwerk-Kameras

01.10.2006 bis 31.12.2007

Surface inspection is of particular importance in industrial production, since the quality of a product can be recognized not only by its functionality but also by its visual representation. The project aims to inspect polymer surfaces with different colors and textures without having to explicitly train a system for a specific surface (color, surface texture).

An intelligent camera with integrated RISC processor and TCP/IP interface was used as optical system.

Solution concept 

The concept is based on methods of texture analysis of homogeneous, weakly granular surfaces. A new algorithm was developed that imitates the behavior of the human visual system. It is assumed that the human observer performs a consistency check in terms of surface homogeneity when viewing and correspondingly perceiving surfaces and makes a decision with respect to object quality based on this result.

For this purpose, a method was investigated and developed which decomposes a surface into homogeneous and non-homogeneous (edges, etc.) regions using directed sum and difference images.

Subsequently, local statistics that are probability density based are extracted from said images. From these, features that are considered representative of the homogeneous surface are derived (median decision of local features). These features are used to adjust a Modified Fuzzy Pattern Classifier (MFPC). It is used for subsequent decision making (classification) in terms of a quality statement regarding a surface.

This project is promoted by:
Stakeholders / Contacts: Dipl.-Ing. Marcus Niederhöfer
Dipl.-Ing. Marcus Niederhöfer¹, Dipl.-Ing. Marcus Niederhöfer, Prof. Dr.-Ing. Volker Lohweg, Prof. Dr.-Ing. Volker Lohweg²
Application-based Approach for Automatic Texture Defect Recognition on Synthetic Surfaces
In: 13th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2008), Sep 2008
¹ First Authors
² Last authors
Research project
Evaluierung von verschiedenen Algorithmen zur Textur-Analyse
Christian Becker