• G. Jayakala
• Dr. L.R. Sudha

Fingerprints are the most widely used unique proofs for recognizing the individuals. In this work, we used human fingerprint images as a confirmation to regulate the classification of person. Fingerprints are broadly used for recognizing individual but gender prediction is a developing field. In this work we used a Deep Convolutional Neural Network (DCNN) to classify the gender classification. This experiment is tested with the internal database of NIST dataset contains 1000 images of size 154×192, where 900 are training image, and 100 are testing image. The Dataset can be classified into two classes: they are (male and female). Experimental results attained 80% in Deep CNN. Thus the deep CNN shows better performance for gender classification using fingerprint images.

Fingerprints, Deep Convolutional Neural Networks, Biometrics and Gender classification

"Fingerprint analysis for gender classification using Deep Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 2, page no.c397-c401, February-2022, Available :http://www.jetir.org/papers/JETIR2202268.pdf

"Fingerprint analysis for gender classification using Deep Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 2, page no. ppc397-c401, February-2022, Available at : http://www.jetir.org/papers/JETIR2202268.pdf