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SZTAKI @ ImageCLEF 2008: Visual Feature Analysis in Segmented Images

  • Bálint Daróczy
  • Zsolt Fekete
  • Mátyás Brendel
  • Simon Rácz
  • András Benczúr
  • Dávid Siklósi
  • Attila Pereszlényi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

We describe our image processing system used in the ImageCLEF 2008 Photo Retrieval and Visual Concept Detection tasks. Our method consists of image segmentation followed by feature generation over the segments based on color, shape and texture. In the paper we elaborate on the importance of choices in the segmentation procedure with emphasis on edge detection. We also measure the relative importance of the visual features as well as the right choice of the distance function. Finally, given a very large number of parameters in our image processing system, we give a method for parameter optimization by measuring how well the similarity measures separate sample images of the same topic from those of different topics.

Keywords

Sample Image Query Expansion Image Processing System Segmentation Procedure Canny Edge Detection 
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 2009

Authors and Affiliations

  • Bálint Daróczy
    • 1
  • Zsolt Fekete
    • 1
  • Mátyás Brendel
    • 1
  • Simon Rácz
    • 1
  • András Benczúr
    • 1
  • Dávid Siklósi
    • 1
  • Attila Pereszlényi
    • 1
  1. 1.Data Mining and Web search Research Group, Informatics LaboratoryComputer and Automation Research Institute of the Hungarian Academy of SciencesHungary

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