Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
525769 | Computer Vision and Image Understanding | 2012 | 12 Pages |
Despite the substantial research into the development of covert iris recognition technologies, no machine to date has been able to reliably perform recognition of human beings in real-world data. This limitation is especially evident in the application of such technology to large-scale identification scenarios, which demand extremely low error rates to avoid frequent false alarms. Most previously published works have used intensity data and performed multi-scale analysis to achieve recognition, obtaining encouraging performance values that are nevertheless far from desirable. This paper presents two key innovations. (1) A recognition scheme is proposed based on techniques that are substantially different from those traditionally used, starting with the dynamic partition of the noise-free iris into disjoint regions from which MPEG-7 color and shape descriptors are extracted. (2) The minimal levels of linear correlation between the outputs produced by the proposed strategy and other state-of-the-art techniques suggest that the fusion of both recognition techniques significantly improve performance, which is regarded as a positive step towards the development of extremely ambitious types of biometric recognition.
► This paper presents a method for the recognition of degraded iris images acquired at visible wavelengths. ► The recognition scheme is based in the definition of homogenous regions inside the iris. ► The description of each region is made by both shape and color MPEG.7 descriptors. ► Minimal levels of linear correlation between the proposed method and state-of-the-art techniques were observed. ► Due to this, significants improvements in performance are obtained when evidence fusion is performed.