• DocumentCode
    169656
  • Title

    Combining Focus Measures through Genetic Algorithm for Shape from Focus

  • Author

    Kaleem, Mohammed ; Mahmood, Muhammad Tariq

  • Author_Institution
    Dept. of Electr. Eng., Comsats Inst. of Inf. Technol., Islamabad, Pakistan
  • fYear
    2014
  • fDate
    6-9 May 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    For the reconstruction of three-dimensional (3D) shape of microscopic objects different focus measure operators have been employed. It is difficult to compute accurate depth map using a single focus measure due to different type of texture. Moreover, real images with diverse types of illumination and contrast lead to the erroneous depth map estimation through a single focus measure. So to address this problem, we have used spatial focus measure operators in conjunction with genetic algorithm for accurate depth map estimation. Genetic algorithm uses the output of the focus measure operators and using weight updating method accurately estimates the depth maps of real world objects. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more useful in computing accurate depth maps as compared to the existing SFF methods.
  • Keywords
    computer vision; genetic algorithms; image reconstruction; image sequences; image texture; shape recognition; 3D shape reconstruction; SFF method; contrast; depth map estimation; genetic algorithm; illumination; image sequences; image texture; microscopic object; shape from focus; single focus measure; spatial focus measure operators; weight updating method; Biological cells; Genetic algorithms; Shape; Sociology; Statistics; Three-dimensional displays; Weight measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2014 International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4799-4443-9
  • Type

    conf

  • DOI
    10.1109/ICISA.2014.6847377
  • Filename
    6847377