Fingerprint based gender classification using discrete wavelet transform (DWT) for Malaysia population

Mahadhir, Majidah (2016) Fingerprint based gender classification using discrete wavelet transform (DWT) for Malaysia population. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

Text (Full text) Fingerprint based gender classification using discrete wavelet transform (DWT) for Malaysia population.pdf - Submitted Version Download (2MB)

Abstract

Biometric authentication systems is developed because each fingerprint structure in person is unique and fingerprints have advantages where it is feasible, differ from each other (distinct), permanent, accurate, reliable and acceptable all over the world for security and person identity. Fingerprints are considered as legal proof of evidence in courts of law all over the world. Frequency domain based fingerprint classification can be done using discrete wavelet transform (DWT), which uses wavelet as its basis function which gives energy based features of an image. We are taking dataset of 50 male and 50 female fingerprints. K-Nearest Neighbors (KNN) classifier is used as for classification and classifies testing fingerprint as male or female fingerprint. This paper describes the overall process of above scheme. DWT transform will give the features of some of the fingerprint images of dataset (training images) to create database of features which will be used as lookup table for classification of unknown fingerprint and other fingerprints.

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