• DocumentCode
    1704374
  • Title

    Optimal supports for image matching

  • Author

    Lew, Michael S. ; Huang, Thomas S.

  • Author_Institution
    Dept. of Comput. Sci., Leiden Univ., Netherlands
  • fYear
    1996
  • Firstpage
    251
  • Lastpage
    254
  • Abstract
    The information theoretic approach provides a foundation for determining new insights and solutions toward image modeling and analysis problems. The underlying principle is that a search through an image can be viewed as a reduction of the expected uncertainty in the classification of the image. Specifically, we propose using the Kullback (1959) relative information for the determination of the support which maximizes the feature class separation, which consequently should minimize the probability of misclassifications. The methods are applied to face detection and two view image matching using internationally available databases
  • Keywords
    face recognition; feature extraction; image classification; image matching; information theory; Kullback relative information; databases; face detection; feature class separation; image analysis; image classification; image matching; image modeling; information theory; misclassification probability; optimal supports; uncertainty reduction; Computer science; Face detection; Image coding; Image matching; Information theory; Maximum likelihood detection; Maximum likelihood estimation; Mutual information; Pixel; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing Workshop Proceedings, 1996., IEEE
  • Conference_Location
    Loen
  • Print_ISBN
    0-7803-3629-1
  • Type

    conf

  • DOI
    10.1109/DSPWS.1996.555508
  • Filename
    555508