Off-angle iris recognition using bi-orthogonal wavelet network system

One important category of non-ideal conditions for iris recognition is off-angle iris images. Practically it is very difficult for images to be captured with no offset. It then becomes necessary to account for off angle information in order to maintain robust performance. A bi-orthogonal wavelet based iris recognition system, previously designed at our lab, is modified and demonstrated to perform off-angle iris recognition. Bi-orthogonal wavelet network (BWN) are developed and trained for each class. The non-ideal factors are adjusted by repositioning the BWN. To test, synthetic iris images are generated by using affine and geometric transforms of 0°, 10° and 20° experimentally collected images from 101 subjects. This approach is shown to perform better than a transformation based iris recognition approach. Iris images off-angle by up to 42° are successfully recognized.