Age dependency of the diabetes effects on the iris recognition systems performance evaluation results
-
Mohammadreza Azimi
,
Seyed Ahmad Rasoulinejad
and
Andrzej Pacut
Abstract
In this paper, we attempt to answer the questions whether iris recognition task under the influence of diabetes would be more difficult and whether the effects of diabetes and individuals’ age are uncorrelated. We hypothesized that the health condition of volunteers plays an important role in the performance of the iris recognition system. To confirm the obtained results, we reported the distribution of usable area in each subgroup to have a more comprehensive analysis of diabetes effects. There is no conducted study to investigate for which age group (young or old) the diabetes effect is more acute on the biometric results. For this purpose, we created a new database containing 1,906 samples from 509 eyes. We applied the weighted adaptive Hough ellipsopolar transform technique and contrast-adjusted Hough transform for segmentation of iris texture, along with three different encoding algorithms. To test the hypothesis related to physiological aging effect, Welches’s t-test and Kolmogorov–Smirnov test have been used to study the age-dependency of diabetes mellitus influence on the reliability of our chosen iris recognition system. Our results give some general hints related to age effect on performance of biometric systems for people with diabetes.
Funding source: Horizon 2020 Framework Programme
Award Identifier / Grant number: 675087
Acknowledgment
The first author is sponsored by the funding source from AMBER with sponsorship from the Marie Sklodowska-Curie EU Framework for Research and Innovation Horizon 2020, under Grant Agreement No. 675087.
Research funding: From AMBER with sponsorship from the Marie Sklodowska-Curie EU Framework for Research and Innovation Horizon 2020, under Grant Agreement No. 675087.
Conflict of interest: The authors have no conflict of interest.
Informed consent: Before the experiment, consent agreements were signed by the participants.
Ethical approval: The experiment specifically designed to investigate that if there is a relation between the iris recognition system’s accuracy and the health condition (diabetes) of the users. All participants were fully informed about the goal and method of the experiment. Before the experiment, consent agreements were signed by all participants. The participants were also asked to provide non-biometric data, including their names, gender, age, and the duration (if applies) of their diabetes illness. The personal data are kept separately to guarantee additional security data. The experiment protocol has been also approved by the Ethics Committee of the Warsaw University of Technology.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Research Articles
- Design of a wearable four-channel near-infrared spectroscopy system for the measurement of brain hemodynamic responses
- Age dependency of the diabetes effects on the iris recognition systems performance evaluation results
- Controlled differential evolution based detection of neovascularization on optic disc using support vector machine
- Workflow and hardware for intraoperative hyperspectral data acquisition in neurosurgery
- EEG-based emotion recognition with deep convolutional neural networks
- Investigating electroencephalography signals of autism spectrum disorder (ASD) using Higuchi Fractal Dimension
- Analysis of autonomic nervous pattern in hypertension based on short-term heart rate variability
- Impact of mandibular prognathism on morphology and loadings in temporomandibular joints
- A new adaptive XOR, hashing and encryption-based authentication protocol for secure transmission of the medical data in Internet of Things (IoT)
- An integrated assessment system for the accreditation of medical laboratories
