Axiom — A Modular Visual Object Retrieval System

  • Jochen Wickel
  • Pablo Alvarado
  • Peter Dörfler
  • Thomas Krüger
  • Karl-Friedrich Kraiss
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2479)


Computer vision has always been an active research domain within artificial intelligence. Recognizing visual objects can alleviate the interaction of users with information retrieval systems. In this paper, we present a modular object recognition system which combines advanced image processing methods with AI techniques in a flexible way. This flexibility permits adaptations to a large variety of tasks. We describe the system architecture, point out some of the key algorithms and present experimental results which demonstrate the system’s performance in several recognition tasks.


Object Recognition Recognition Rate Training Image Radial Basis Function Neural Network Color Channel 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jochen Wickel
    • 1
  • Pablo Alvarado
    • 1
  • Peter Dörfler
    • 1
  • Thomas Krüger
    • 1
  • Karl-Friedrich Kraiss
    • 1
  1. 1.Lehrstuhl für Technische InformatikRWTH AachenGermany

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