  Fingerphoto images captured using a smartphone are successfully used to
verify the individuals that have enabled several applications. This work
presents a novel algorithm for fingerphoto verification using a nested residual
block: Finger-NestNet. The proposed Finger-NestNet architecture is designed
with three consecutive convolution blocks followed by a series of nested
residual blocks to achieve reliable fingerphoto verification. This paper also
presents the interpretability of the proposed method using four different
visualization techniques that can shed light on the critical regions in the
fingerphoto biometrics that can contribute to the reliable verification
performance of the proposed method. Extensive experiments are performed on the
fingerphoto dataset comprised of 196 unique fingers collected from 52 unique
data subjects using an iPhone6S. Experimental results indicate the improved
verification of the proposed method compared to six different existing methods
with EER = 1.15%.
