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Herausgeber: 
  • Etienne E. Kerre
  • Mike Nachtegael
  • Dietrich Van der Weken
  • Dimitri Van De Ville
  • Fuzzy Filters for Image Processing 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2010  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Applications of Mathematics / Applied mathematics / C / Computer modelling & simulation / computer science / Computer simulation / Computer Vision / engineering / Engineering mathematics / Image processing / Image Processing and Computer Vision / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Optical data processing / Simulation and Modeling
    ISBN:  9783642055911 
    EAN-Code: 
    9783642055911 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #122 - Studies in Fuzziness and Soft Computing  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  1240 gr 
    Seiten:  386 
    Illustration:  XIV, 386 p. 518 illus., 13 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  Previously published in hardcover 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The ongoing increase in scale of integration of electronics makes storage and computational power affordable to many applications. Also image process­ ing systems can benefit from this trend. A variety of algorithms for image processing tasks becomes close at hand. From the whole range of possible approaches, those based on fuzzy logic are the ones this book focusses on. A particular useful property of fuzzy logic techniques is their ability to represent knowledge in a way which is comprehensible to human interpretation. The theory of fuzzy sets and fuzzy logic was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from mem­ bership to nonmembership, providing partial degrees of membership. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. The present book resulted from the workshop "Fuzzy Filters for Image Processing" which was organized at the 10th FUZZ-IEEE Conference in Mel­ bourne, Australia. At this event several speakers have given an overview of the current state-of-the-art of fuzzy filters for image processing. Afterwards, the book has been completed with contributions of other international re­ searchers.
      
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