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Linguistic Description of Relative Positions in Images

Pascal Matsakis James M. Keller Laurent Wendling 1 Jonathon Marjamaa Ozy Sjahputera
1 ISA - Models, algorithms and geometry for computer graphics and vision
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Fuzzy set methods have been used to model and manage uncertainty in various aspects of image processing, patternr recognition and computer vision. High-level computer vision applications hold a great potential for fuzzy set theory because of its links to natural language. Linguistic scene description, a language-based interpretation of regions and their relationships, in one such application that is starting to bear the fruits of fuzzy set theoric involvment. In this paper, we are expanding on two earlier endeavors. We introduce new families of histograms of forces. These families preserve important relative position properties. They provide inputs to a fuzzy rule base that produces logical linguistic descriptions along with assessments as to the validity of the descriptions. Each linguistic output uses hedges from a dictionary of about 30 adverbs and other terms that can be tailored to individual users. Excellent results from several synthetic and real image examples show the applicability of this approach.
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https://hal.inria.fr/inria-00100498
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Submitted on : Tuesday, September 26, 2006 - 2:46:15 PM
Last modification on : Friday, February 26, 2021 - 3:28:03 PM

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Pascal Matsakis, James M. Keller, Laurent Wendling, Jonathon Marjamaa, Ozy Sjahputera. Linguistic Description of Relative Positions in Images. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Institute of Electrical and Electronics Engineers, 2001, 31 (4), pp.573-588. ⟨inria-00100498⟩

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