• DocumentCode
    2772853
  • Title

    An Invariant Approach for Image Recognition

  • Author

    Zuniga-Segura, Erick ; Sánchez-Díaz, Guillermo

  • Author_Institution
    Center of Technol. Res. on Inf. & Syst., UAEH, Pachuca
  • Volume
    2
  • fYear
    2006
  • fDate
    Sept. 2006
  • Firstpage
    30
  • Lastpage
    34
  • Abstract
    Shape-of-object representation has always been an important topic in image processing and pattern recognition. This work deals with representation of shape of objects, and approaches to recognize objects. Several invariant techniques are widely used to represent an object because they preserve information and allow considerable data reduction. In this paper, a new approach based on a code representation and testor theory is presented. The proposed method is invariant under translation, scaling and rotation. Also, the paper discusses the capabilities of the method in recognizing objects. In addition, results using simple figures classes are show
  • Keywords
    computer vision; image recognition; image representation; object recognition; code representation; computer vision; image processing; image recognition; image tester theory; object recognition; pattern recognition; shape-of-object representation; Application software; Computer vision; Image processing; Image recognition; Image representation; Logic testing; Machine learning; Machine vision; Pattern recognition; Shape; Computer Vision; Invariants; logical combinatorial pattern recognition.; testors theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Robotics and Automotive Mechanics Conference, 2006
  • Conference_Location
    Cuernavaca
  • Print_ISBN
    0-7695-2569-5
  • Type

    conf

  • DOI
    10.1109/CERMA.2006.14
  • Filename
    4019766