Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children.
Reference:
Nelufule, N. et al. 2019. Image quality assessment for iris biometrics for minors. In: Information Communication Technology and Society Conference (ICTAS), Blue waters Hotel Durban, 6-8 March 2019
Nelufule, N. (2019). Image quality assessment for iris biometrics for minors. IEEE. http://hdl.handle.net/10204/11357
Nelufule, Nthatheni. "Image quality assessment for iris biometrics for minors." (2019): http://hdl.handle.net/10204/11357
Nelufule N, Image quality assessment for iris biometrics for minors; IEEE; 2019. http://hdl.handle.net/10204/11357 .
Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website.
