An Iris Feature Extraction Using 2D-Dual Tree Complex Wavelet Transform
Ajita Singh1, Jayesh Gangrade2
1Ajita Singh, Department of Computer Science, Institute of Engineering, IPS, Academy, Indore, India.
2Prof. Jayesh Gangrade, Associate Professor, CSE, IES, IPSA, Indore, India.
Manuscript received on July 24, 2013. | Revised Manuscript received on August 04, 2013. | Manuscript published on August 30, 2013. | PP: 47-51 | Volume-2, Issue-6, August 2013. | Retrieval Number: F1948082613/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents an iris recognition system consists of an automatic segmentation system that is based on the 2D-Dual tree complex wavelet transform(2D-CWT), and is able to localize the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region was then normalized into a rectangular block with constant dimensions to account for imaging inconsistencies. Finally, the data was extracted and quantized to four levels to encode the unique pattern of the iris into a bit-wise biometric template. The K-nearest neighbor technique was employed for classification of iris templates. The obtained experimental results showed that the proposed approach enhanced the classification accuracy. Iris verification is shown to be a reliable and accurate biometric technology.
Keywords: Iris recognition, Dual-Tree Complex Wavelet Transform, Biometrics.