@article{1434,
  author = {Mazhar Sajjad, Jin-Woo Jung},
  title = {Iris Image Enhancement for Biometric Personal Identification},
  journal = {Journal of Intelligent Computing},
  year = {2013},
  volume = {4},
  number = {2},
  doi = {},
  url = {http://www.dline.info/jic/fulltext/v4n2/4.pdf},
  abstract = {Obtaining an iris image under uncontrolled and facing non friendly users, the chances of acquiring non ideal images is very high due to poor focus, off-angle, noise, and motion blur, occlusion of eyelashes and eyelids and wearing glasses. In order to improve the quality of these images, we propose a method which improves the quality of degraded iris images and ultimately improve the recognition accuracy. In the first step the iris image is localized, and then normalized the iris image to get the fixed size. In the second step, the valid region (iris region) is extracted from the segmented iris image so that to get only the iris region. In order to get well distributed texture image, bilinear interpolation is used to the segmented valid iris gray image. The low contrast of the resulted interpolated image is enhanced by histogram equalization. The 1D Gabor filter is applied to the gray image channels and gray texture information is extracted by 1D Gabor filter. And, the Hamming distance is chosen as a metric for recognition. The NICE-II training dataset taken from UBRIS.v2 was used for the experiment. The proposed method shows more enhanced performance in the aspect of FAR (False Acceptance Rate), FRR (False Rejection Rate) and EER (Equal Error Rate).},
}