Region based feature extraction from non-cooperative iris images using triplet half-band filter bank

highlights•A multi-resolution analysis based technique is studied for iris feature extraction.•We have proposed a new class of THFB using a half-band polynomial of order 10.•The proposed filter bank is found to have improved frequency selectivity.•Energy features are extracted from normalized iris image.•The performance of the system is found to be better than existing techniques.

In this paper, we have proposed energy based features using a multi-resolution analysis (MRA) on iris template. The MRA is based on our suggested triplet half-band filter bank (THFB). The THFB derivation process is discussed in detail. The iris template is divided into six equispaced sub-templates and two level decomposition has been made to each sub-template using THFB except second one. The reason for discarding the second template is due to the fact that it mostly contains the noise due to eyelids, eyelashes, and occlusion due to segmentation failure. Subsequently, energy features are derived from the decomposed coefficients of each sub-template. The proposed feature has been experimented on standard databases like CASIAv3, UBIRISv1, and IITD and mostly on iris images which encounter a segmentation failure. Comparative analysis has been done with existing features based on Gabor transform, Fourier transform, and CDF 9/7 filter bank. The proposed scheme shows superior performance with respect to FAR, GAR and AUC.