Feature Selection for Iris Recognition with AdaBoost

  • Authors:
  • Kan-Ru Chen;Chia-Te Chou;Sheng-Wen Shih;Wen-Shiung Chen;Duan-Yu Chen

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 02
  • Year:
  • 2007

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Abstract

In this paper, we proposed a method for selecting edge- type features for iris recognition. The AdaBoost algorithm is used to select a filter bank from a pile of filter candi- dates. The decisions of the weak classifiers associated with the filter bank are linearly combined to form a strong clas- sifier. Real experiments have been conducted to assess the performance of the designed strong classifier. The results showed that the boosting algorithm can effectively improve the recognition accuracy at the cost of slightly increase the computation time. Keywords: Iris Recognition, Biometrics, Feature Extrac- tion, AdaBoost.