Iris recognition using wavelet features
- Authors
- Kim, J; Cho, SW; Choi, J; Marks, RJ
- Issue Date
- Sep-2004
- Publisher
- SPRINGER
- Keywords
- iris recognition; continuous wavelet transform; feature representation; curve optimization
- Citation
- JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, v.38, no.2, pp.147 - 156
- Journal Title
- JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
- Volume
- 38
- Number
- 2
- Start Page
- 147
- End Page
- 156
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/25750
- DOI
- 10.1023/B:VLSI.0000040426.72253.b1
- ISSN
- 0922-5773
- Abstract
- The traditional iris recognition systems require equal high quality human iris images. A cheap image acquisition system has difficulty in capturing equal high quality iris images. This paper describes a new feature representation method for iris recognition robust to noises. The disc-shaped iris image is first convolved with a low pass filter along the radial direction. Then, the radially smoothed iris image is decomposed in the angular direction using a one-dimensional continuous wavelet transforrn. Each decomposed one-dimensional waveform is approximated by an optimal piecewise linear curve connecting a small set of node points. The set of node points is used as a feature vector. The optimal approximation procedure reduces the feature vector size while maintaining recognition accuracy. The similarity between two iris images is measured by the normalized cross-correlation coefficients between optimal curves. The similarity between two iris images is estimated using mid-frequency bands. The rotation of one-dimensional signals due to the head tilt is estimated using the lowest frequency component. Experimentally we show the proposed method produces superb performance in iris recognition.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Engineering > School of Electronic & Electrical Engineering > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/25750)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.