Orientation selective contour detection using oriented motion blur

Barna Resko, Péter Baranyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cognitive informatics is a very hot topic today, trying to provide solutions to problems in computation that are easily solved by the brain but are hard for a computer. The information processing properties of the brain are taken as the basis for such artificial systems. The first step of visual information processing, the extraction of orientation selective contours, is done in the primary visual cortex. A similar, orientation based filtering can be the first step in many vision systems of cognitive informatics. This paper presents a new approach to orientation selective contour detection. Oriented motion blur is used to filter for the desired orientations. The motion blur operation is performed before digitalization, using a vibrating mirror. The proposed technique not only provides a very high speed, high resolution contour detector, but also solves the problem of contour discontinuities.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence and Pattern Recognition 2007, AIPR 2007
Pages272-277
Number of pages6
Publication statusPublished - Dec 1 2007
Event2007 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2007 - Orlando, FL, United States
Duration: Jul 9 2007Jul 12 2007

Publication series

NameInternational Conference on Artificial Intelligence and Pattern Recognition 2007, AIPR 2007

Other

Other2007 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2007
CountryUnited States
CityOrlando, FL
Period7/9/077/12/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

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    Resko, B., & Baranyi, P. (2007). Orientation selective contour detection using oriented motion blur. In International Conference on Artificial Intelligence and Pattern Recognition 2007, AIPR 2007 (pp. 272-277). (International Conference on Artificial Intelligence and Pattern Recognition 2007, AIPR 2007).