IRIS recognition in visible light domain

Present iris recognition techniques allow very high recognition performances in controlled settings and with cooperating users; this makes iris a real competitor to other biometric traits like fingerprints, with the further advantage of requiring a contactless acquisition. Moreover, most of the existing approaches are designed for Near Infrared or Hyperspectral images, which are less affected by changes in illumination conditions. Current research is focusing on designing new techniques aiming to ensure high accuracy even on images acquired in visible light and in adverse conditions. This paper deals with an approach to iris matching based on the combination of local features: Linear Binary Patterns (LBP) and discriminable textons (BLOBs). Both these technique have been readapted in order to deal with images captured in variable visible light conditions, and affected by noise due to distance/resolution or to scarce user collaboration (blurring, off-axis iris, occlusion by eyelashes and eyelids). The obtained results are quite convincing and strongly motivate the addition of more local features.