Face-palm print recognition system based on 2d circular wavelet Filter and contourlet transformation

Year 2023, Volume: 2 Issue: 2, 247 - 252, 27.12.2023

Zahraa Talal Ahmed M. Alkababji

Abstract

The study proposes a multimodal biometric design that combines face and palm print recognition modules. To extract the features from the face data set, we proposed a novel 2-D circular wavelet filter that depends on HAAR filters and used the contourlet transformation in palm print data sets. The multimodal biometric design merges the features extracted from different types of unimodal system UBS by using a fusion level. Our proposed approach wants to decrease the time required to recognize a person depending on 2-D CDWT and enhance the accuracy of recognition by using the 2-D CDWT and contourlet transformations as pre-processing level in our approach, then the CNN model is applied to train and test our approach. Our data set was taken from 110 persons which means 1100 pairs of images in 10 sessions. This approach’s results look good and progressed over other most recent architectures by recording a precision of 99.3%, with a score-level fusion.

Keywords

face recognition, palm print recognition, multimodal biometric system, 2D circular wavelet filter, and contourlet transformation.

Supporting Institution

no supporting institution

Project Number

ICES-225

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