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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 11386
School of Cognitive Sciences
  Title:   Feature Fusion as a Practical Solution toward Noncooperative Iris Recognition
1 . N. Tajbakhsh
2 . Babak Nadjar Arabi
3 . Hamid Soltanianzadeh
  Status:   In Proceedings
  Proceeding: Presented at and Published in the Proceeding of the 11th International Conference on Information Fusion, Cologne, Germany, June 30-July 3, 2008
  Year:  2008
  Supported by:  IPM
In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

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