Basic Image Features (BIFs) Arising from Approximate Symmetry Type

  • Authors:
  • Lewis D. Griffin;Martin Lillholm;Mike Crosier;Justus Sande

  • Affiliations:
  • Computer Science, University College London, London, UK WC1E 6BT;Computer Science, University College London, London, UK WC1E 6BT;Computer Science, University College London, London, UK WC1E 6BT;Biomedical Engineering, Eindhoven University of Technology, The Netherlands

  • Venue:
  • SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
  • Year:
  • 2009

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Abstract

We consider detection of local image symmetry using linear filters. We prove a simple criterion for determining if a filter is sensitive to a group of symmetries. We show that derivative-of-Gaussian (DtG) filters are excellent at detecting local image symmetry. Building on this, we propose a very simple algorithm that, based on the responses of a bank of six DtG filters, classifies each location of an image into one of seven Basic Image Features (BIFs). This effectively and efficiently realizes Marr's proposal for an image primal sketch. We summarize results on the use of BIFs for texture classification, object category detection, and pixel classification.