DocumentCode
2820443
Title
Iris recognition using discrete wavelet transform and artificial neural networks
Author
Abdel Alim, Ons ; Shar, Maha
Author_Institution
Facult of Eng., Alexandria Univ., Egypt
Volume
1
fYear
2003
fDate
27-30 Dec. 2003
Firstpage
337
Abstract
The iris of the human eye has a highly detailed pattern which is unique for each individual and stable over years. It is now considered as an important and reliable biometric tool for personal identification. A new technique for extracting iris texture using the 2D-DWT at different decomposition levels is suggested. Recognition rates of about 95% have been achieved using ANN classifiers.
Keywords
biometrics (access control); discrete wavelet transforms; eye; feature extraction; image recognition; image texture; neural nets; ANN classifiers; artificial neural networks; biometric tool; decomposition level; discrete wavelet transform; human eye; iris recognition; iris texture; personal identification; recognition rate; Artificial neural networks; Biometrics; Discrete cosine transforms; Discrete wavelet transforms; Eyelids; Feature extraction; Fingerprint recognition; Humans; Iris recognition; Reliability engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2003 IEEE 46th Midwest Symposium on
ISSN
1548-3746
Print_ISBN
0-7803-8294-3
Type
conf
DOI
10.1109/MWSCAS.2003.1562287
Filename
1562287
Link To Document