• DocumentCode
    2903081
  • Title

    Similarity of iris texture between siblings

  • Author

    Vranderic, Will ; Bowyer, Kevin W.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, Notre Dame, IN, USA
  • fYear
    2013
  • fDate
    Sept. 29 2013-Oct. 2 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Prior research has shown that twins´ irises are similar enough in appearance for the untrained human observer to correctly determine whether an iris image pair comes from twins or from unrelated persons. We conducted a similar image pair classification study that asked participants to classify an image pair as “siblings” or “unrelated”. We found that untrained human observers can classify pairs of siblings with over 57% accuracy using the appearance of the iris alone, without any proximal image content. This result is statistically greater than the accuracy of random guessing, which indicates that there is some degree of inherited texture similarity between siblings. This raises the question of how accurately one could classify siblings based on automated texture analysis.
  • Keywords
    image classification; image texture; iris recognition; automated texture analysis; iris image pair classification; iris texture similarity; sibling classification; Accuracy; Data acquisition; Educational institutions; Image segmentation; Iris; Iris recognition; Observers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on
  • Conference_Location
    Arlington, VA
  • Type

    conf

  • DOI
    10.1109/BTAS.2013.6712753
  • Filename
    6712753