Deformable DAISY Matcher for robust iris recognition
Man Zhang, Zhenan Sun, Tieniu Tan · 2011
Iris is rich of texture information for reliable personal identification. However, nonlinear deformation of iris pattern caused by pupil dilation or contraction raises a grand challenge to iris recognition. This paper proposes a novel iris recognition method namely Deformable DAISY Matcher (DDM) for robust iris feature matching. Firstly, dense DAISY descriptors are extracted to represent regional iris features, which are robust against intra-class variations of iris images. Then a set of iris key points are localized on the feature map. Finally deformation tolerant matching strategy is proposed to match corresponding key points of iris images. Experimental results on two iris image databases demonstrate DDM is better than state-of-the-art iris recognition methods.