A Survey: Iris Recognition Techniques & Predict Gender from Iris Images

  Rehana Parwin,  Swati Verma

This paper employs machine learning techniques to develop models that predict gender based on the iris texture features. While there is a large body of research that explores biometrics as a means of verifying identity, there has been very little work done to determine if biometric measures can be used to determine specific human attributes. If it is possible to discover such attributes, they would be useful in situations where a biometric system fails to identify an individual that has not been enrolled, yet still needs to be identified. The iris was selected as the biometric to analyze for two major reasons: (1) quality methods have already been developed to segment and encode an iris image; (2) current iris encoding methods are conducive to selecting and extracting attributes from an iris texture and creating a meaningful feature vector. Among various biometric authentication systems iris recognition system is considered to be more accurate and reliable. The main objective of these systems is to identify the user as an authentic or an imposter. These systems does not reveal about imposter’s gender or ethnicity. Majority of practices for gender classification utilize facial information. Very few references in the literature reported the identification of human attributes such as gender with the help of iris images. In this paper gender has been identified using iris images.

Keywords- gender classification, iris, biometric

Unique Identification Number - IJEDR1503131
Page Number(s) - 1-4
Pubished in - Volume 3 | Issue 3 | Sept 2015
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Rehana Parwin,  Swati Verma,   "A Survey: Iris Recognition Techniques & Predict Gender from Iris Images", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 3, pp.1-4, Sept 2015, Available at :http://www.ijedr.org/papers/IJEDR1503131.pdf