• DocumentCode
    3039693
  • Title

    Object Identification Based on Deformable Templates and Genetic Algorithms

  • Author

    Moni, M.A. ; Ali, A. B M Shawkat

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Jatiya Kabi Kazi Nazrul Islam Univ., Bangladesh
  • fYear
    2009
  • fDate
    24-26 July 2009
  • Firstpage
    114
  • Lastpage
    117
  • Abstract
    In this paper, an algorithm is described which detects and localizes shapes in grayscale images. Deformable templates are often employed to model the geometry of the object to be found in an image. There are several methods to find the optimal placement and deformation of the template onto the image. A genetic algorithm is designed which takes the object template and processed grayscale image and locates the object in the image, invariant to rotation, translation and scale. The limitations of processing the image before running the genetic algorithm (GA) are discussed.
  • Keywords
    edge detection; genetic algorithms; object recognition; Canny edge detection; deformable templates; evolutionary algorithm; genetic algorithms; grayscale images; object identification; object recognition system; Algorithm design and analysis; Deformable models; Evolutionary computation; Genetic algorithms; Genetic engineering; Genetic mutations; Geometry; Gray-scale; Object recognition; Solid modeling; Deformable templates; Evolutionary algorithm; Genetic algorithm; Object identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-0-7695-3705-4
  • Type

    conf

  • DOI
    10.1109/BIFE.2009.198
  • Filename
    5208922