A Semi-local Topological Constraint for Efficient Detection of Near-Duplicate Image Fragments

  • Mariusz Paradowski
  • Andrzej Śluzek
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)


Image matching methods are an important branch of computer vision and have many possible applications, i.e. robotics, navigation, etc. Their goal is to detect near-duplicate images, sub-images or even localize image fragments. The paper addresses the last, and the most difficult problem: simultaneous localization of multiple image fragments in images of unknown content. A complete lack of any a priori knowledge is assumed, including no information of the number of fragments. The presented approach combines low level vision techniques and high level spatial constraints. Photometric properties of the images are represented using key-regions. Spatial consistency is verified using the topology of images. A graph of topologically consistent key-regions is created. It allows efficient localization of entire near-duplicate image fragments.


Neighborhood Size Topological Graph High Computational Complexity Topological Constraint Spatial Neighborhood 
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 2011

Authors and Affiliations

  • Mariusz Paradowski
    • 1
    • 2
    • 3
  • Andrzej Śluzek
    • 1
    • 2
    • 3
  1. 1.Institute of InformaticsWroclaw University of TechnologyPoland
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingapore
  3. 3.Faculty of Physics, Astronomy and InformaticsNicolaus Copernicus UniversityPoland

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