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
fDate :
Sept. 29 2013-Oct. 2 2013
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;
Conference_Titel :
Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on
Conference_Location :
Arlington, VA
DOI :
10.1109/BTAS.2013.6712753