Technology Offers

Optimized filters for image feature recognition, e.g. for surface inspection

Abstract

With these customized filter banks, error classifications with significantly higher selectivity and better detection rates can be achieved. The method can be easily integrated as software into existing systems for surface inspection.

Background

The recognition and extraction of image features, i.e. their general classification, plays a major role in digital image processing. For example, for surface inspection, images are taken of surfaces in order to identify different classes of surface defects. However, objects of the same class may occur in various sizes, which poses a challenge to the con­ventional image processing methods available. Solutions that are actually adapted to the respective image feature would considerably improve the reliability and sta­bility of these analysis methods.

Problem

The dyadic and M-channel wavelet filter banks that have been widely used cannot be optimally matched to the dif­fer­ent sizes of the image features due to their integer scal­ing. That means their use is far from satisfactory for all kinds of applications.

Solution

The filter process according to the invention was developed within the framework of a research project carried out by the University of Applied Sciences Pforzheim in coopera­tion with the Fraunhofer Institute IOSB and the Karlsruhe Institute of Technology KIT. It uses tailored "rational biorthogonal wavelet filter banks". The design is carried out in two steps: first the most suitable rational scaling factor is determined and then the filter coefficients are matched to the image characteristics. Biorthogonal filters are used to create higher degrees of freedom.
The new analysis method was tested in a series using deflectometry for the detection of defects on specular sur­faces. The method achieved a much higher degree of selectivity in defect classification than conventional meth­ods. The corresponding detection rates are also superior to those of known methods. This is illustrated by the figure showing exemplary test results. The invention concerns this method of analysis as well as its implementation into existing systems. The customized filter banks can be inte­grated into existing systems to optimize feature recogni­tion.

Tables that illustrate the increas of classification results and the advantage of differently structured RWFBs
The left table shows an increase of classification results due to the increased number of attributes (t) considered for an object and illustrates the advantage of rational biorthogonal filter banks (RWFB) over M-channel filter banks (MCFB). The table on the right illustrates the advantage of differently structured RWFBs (below) over the use of "thresholding" or standard wavelets (above). The accuracy of the classifications for the feature classes Cd (dent), Cp (pimple) as well as Cs (stain) is shown, taking into account different resolution levels t.

Advantages

  • Significantly higher detection rates and selectivity in the classification of image features
  • Filter banks and their components are specifically adapted to characteristic features
  • New software can be easily integrated into existing systems and processes

Application

  • Quality control (defect detection on surfaces)
  • Digital image processing

Find out more

Thomas Greiner, Tan-Toan Le, Mathias Ziebarth, Michael Heizmann, Multiskalige Oberflächeninspektion mit Wavelets und Deflektometrie, tm-Technisches Messen, Band 83, Heft 11, Seiten 617–627, ISSN (Online) 2196-7113, ISSN (Print) 0171-8096, October 2016, De Gruyter Verlag.
DOI: https://doi.org/10.1515/teme-2015-0047

Tan-Toan Le, Matthias Ziebarth, Thomas Greiner, Michael Heizmann, Systematic Design of Object Shape Matched Wavelet Filter Banks for Defect Detection, 39th International Conference on Telecommunications and Signal Processing, June 2016, Vienna, Austria.
DOI: https://doi.org/10.1109/TSP.2016.7760923

Le, T.-T.; Ziebarth, M.; Greiner, T.; Heizmann, M.: Optimized Size-adaptive Feature Extraction Based on Content-matched Rational Wavelet Filters. - ln: Proceedings of the 22th European Signal Processing Conference (EUSIPCO), Lisbon Portugal, September 2014, pp. 1672-1676. (978-0-9928626-1-9).

T. Le, T. Greiner, M. Ziebarth, M. Heizmann, Inspection of Specular Surfaces using Optimized M-Channel Wavelets, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Proceedings, Vancouver, Canada, May 2013.

Exposé
Contact
Anne Böse, M.Sc.
TLB GmbH
Ettlinger Straße 25
76137 Karlsruhe | Germany
Phone +49 721-79004-0
boese(at)tlb.de | www.tlb.de
Development Status
Prototype
Patent Situation
EP 2977933 B1 granted
DE granted
FR granted
GB granted
Reference ID
14/005TLB
Service
TLB GmbH manages inventions until they are marketable and offers companies opportunities for license and collab­oration agreements.