Gender Detection and Classification from Fingerprints Using Pixel Count

5 Pages Posted: 29 Aug 2019 Last revised: 20 Oct 2019

See all articles by Anju

Anju

Government College of Engineering Kannur

Sajith

Government College of Engineering Kannur

Date Written: August 28, 2019

Abstract

In this modern world of technology, gender classification have immense value. Gender detection from the fingerprint helps to catalogue the data and to analyze it easily. Now a days gender detection based on fingerprint can be seen in industrial, commercial and unique id of nation as AADHAR card. Today, world’s judicial system accepted Fingerprint based recognition of an individual and it is the most adopted technique. So in this work we tried to implement a system to detect the gender of the particular fingerprint. In this proposed system, time domain approach is used to find out the gender of a particular fingerprint obtained using systematic pixel counting. The results showed that the gender identification using systematic pixel counting have 90.2% classification accuracy for females and 96.4% for males. The algorithm can be developed using Python framework 3.6.

Keywords: human fingerprints, ridge count, valley area, threshold, gender classification

Suggested Citation

Narayanan, Anju and K, Sajith, Gender Detection and Classification from Fingerprints Using Pixel Count (August 28, 2019). In proceedings of the International Conference on Systems, Energy & Environment (ICSEE) 2019, GCE Kannur, Kerala, July 2019. Available at SSRN: https://ssrn.com/abstract=3444032 or http://dx.doi.org/10.2139/ssrn.3444032

Anju Narayanan (Contact Author)

Government College of Engineering Kannur ( email )

Kannur
India

Sajith K

Government College of Engineering Kannur ( email )

Kannur
India

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