Title :
Iris recognition using self-organizing neural network
Author :
Liam, Lye Wil ; Chekima, Mi ; Fan, Liau Chung ; Dargham, Jamahmad
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. Malaysia Sabah, Malaysia
Abstract :
Among biometric systems for user verification, iris recognition systems represent a relatively new technology. Our system consists of two main parts: a localizing iris and iris pattern recognition. The raw image is captured using a digital camera. The iris is then extracted from the background after enhancement and noise elimination. Due to noise and the high degree of freedom in the iris pattern, only parts of the iris structure are selected for recognition. The selected iris structure is then reconstructed into a rectangle format. Using a trained self-organizing map neural network, iris patterns are recognized. The overall accuracy of our network is found to be about 83%.
Keywords :
biometrics (access control); eye; feature extraction; image denoising; image enhancement; image recognition; image reconstruction; self-organising feature maps; biometric systems; digital camera; enhancement; iris extraction; iris pattern recognition; iris recognition; localizing iris; neural network accuracy; noise elimination; raw image capture; rectangle format; selected iris structure reconstruction; self-organizing neural network; trained self-organizing map neural network; user verification; Biometrics; Digital cameras; Eyelids; Fingerprint recognition; Image reconstruction; Information technology; Iris recognition; Neural networks; Pattern recognition; Shape;
Conference_Titel :
Research and Development, 2002. SCOReD 2002. Student Conference on
Print_ISBN :
0-7803-7565-3
DOI :
10.1109/SCORED.2002.1033084
