A Multimodal Biometric Identification Approach using Machine Learning

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.8 · Issue 4

Published

November 2019

Access

Open Access

Licence

CC BY-NC-SA 4.0

Keshav Kumar Joshi Ankita Bhargava Dr. Prashant Sharma

Unimodal biometric systems have been in existence for some years, but are rather adapted to an average level of security. In fact, the higher the level of security, the more one will tend towards the use of multimodal systems, more efficient and safer. This paper develops an approach of multimodal biometric identification system from the fusion of Discrete Wavelet Transform (DWT) features of the face and fingerprint images along with the Gabor wavelet and wavelet moment features of Iris image and performing the results with Random Forest Classifier. Performance evaluation is done using a confusion matrix plot with sensitivity, specificity, and accuracy.

DWT Gabor Wavelet Wavelet Moment Random Forest Classifier

Keshav Kumar Joshi, Ankita Bhargava, Dr. Prashant Sharma (2019). A Multimodal Biometric Identification Approach using Machine Learning. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.8, Issue 4. ISSN: 2319-4863.

Copy Citation

Full references are available in the PDF version of this paper.

Download Full Paper (PDF) →

Downloads

Full Text Access

Full Paper

PDF Download

Abstract PDF

PDF Download

Article Info

LinkedIn Twitter / X WhatsApp