Iris-Pupil Thickness based Biometric Approach for Determining Age Group using Linear SVM

• Published in: 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT) pp. 275 - 279
• Main Authors: Ferdous, Mst. Jannatul, Turzo, Nakib Aman, Sarker, Pritom
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28-11-2020
• Subjects: Age group detection; Data mining; Image segmentation; Information and communication technology; Inner-outer boundary of iris; Iris classification; Iris recognition; Iris-pupil ratio; Logistics; Support vector machine classification; SVM-Support Vector Machine; Training
• DOI: 10.1109/ICAICT51780.2020.9333516

Age group prediction using the ratio of iris-pupil has become a new concept. As every human iris has some individual properties. But for a similar age group such as young or adult has nearly a common range of iris-pupil ratio. By using this potential feature of the iris, the proposed system tries to predict a certain range of the ratio for these age groups. In this paper, by analyzing the iris-pupil ratio from iris images after segmentation, the training and classification obtained the results using SVM, Logistic Regression, etc. some popular methods of Data Mining. This research work founds some certain changes like the ratio of iris-pupil that increases young to adult. The results represent greater accuracy than previously used different statistical techniques and less time-consuming. So, it might proclaim that to distinguish age groups of humans this approach is methodical and at the same time is very meteoric.