Neural Network Based Human Age-group Estimation in Curvelet Domain

In this paper we investigate whether human digital fingerprints can be used to estimate human age-groups. To our knowledge, human age-group estimation using digital fingerprints have not been addressed formally. Human age-group estimation can be applied in the areas of online child protection, age based access control or customized services based on estimated age-groups. Motivated by the fact that human digital fingerprint vary in width ranging from birth to adulthood but pattern remains the same, we have developed a procedure to extract discriminating features using Curvelet Transform to classify fingerprints into three age groups. Experimental results show the feasibility of our method which can be used to protect children over cyberspace by automatically customizing their access according to their age-group.