title: Iris recognition based on key image feature extraction.
abstract: In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.
authors.affiliation: Biomechanics & Medical Information Institute, Beijing University of Technology, Beijing, People's Republic of China.
authors.forename: X
authors.initials: X
authors.lastname: Ren
authors.forename: Q
authors.initials: Q
authors.lastname: Tian
authors.forename: J
authors.initials: J
authors.lastname: Zhang
authors.forename: S
authors.initials: S
authors.lastname: Wu
authors.forename: Y
authors.initials: Y
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D016000:Cluster Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007498:Iris / Q000033:anatomy & histology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity