An Iris Feature Extraction Using 2D-Dual Tree Complex Wavelet Transform

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.