Title :
Feature-domain super-resolution for iris recognition
Author :
Nguyen, Kien ; Fookes, Clinton ; Sridharan, Sridha ; Denman, Simon
Author_Institution :
Image & Video Res. Lab., Queensland Univ. of Technol., Brisbane, QLD, Australia
Abstract :
Uncooperative iris identification systems at a distance suffer from poor resolution of the captured iris images, which significantly degrades iris recognition performance. Super-resolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, all existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values. This paper considers transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. This is the first paper to investigate the possibility of feature-domain super-resolution for iris recognition, and experiments confirm the validity of the proposed approach.
Keywords :
feature extraction; image enhancement; image resolution; iris recognition; biometric super-resolve pixel intensity; feature domain super-resolution; image enhancement; image resolution; iris recognition; pixel domain super-resolution; Estimation; Face recognition; Image recognition; Image resolution; Iris recognition; Signal resolution; Vectors; feature-domain super-resolution; iris recognition; iris recognition at a distance; super-resolution;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116348