Multi-level Fusion of Palmprint and Dorsal Hand Vein

Chaudhary, Gopal; Srivastava, Smriti; Bhardwaj, Saurabh

doi:10.1007/978-81-322-2755-7_34

Cited by 10 publications

(1 citation statement)

References 13 publications

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“…•Touchless palm photo dataset [29] (DB2) consists of a total of 1344 images from 168 different people [8 images from each hand] taken with a digital camera at an image resolution of1600x1200 pixels. The images in the dataset that our proposed approach StyleGAN2-ADA prefers to be square.…”

Section: Datasetmentioning

confidence: 99%

Advancements in Synthetic Generation for Contactless Palmprint Biometrics Using StyleGan2-ADA and StyleGAN3

Chowdhury,

Khondkar,

Imtiaz

2023

Preprint

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In addressing the challenges of data scarcity in biometrics, this study explores the generation of synthetic palmprint images as an efficient, cost effective, and privacy preserving alternative to real-world data reliance. Traditional methods for synthetic biometric image creation primarily involve orientation modifications and filter applications, with no established method specific to palmprints. We introduced the utilization of the “Style-based generator”, StyleGAN2-ADA, from the StyleGAN series, renowned for generating high-quality images. Furthermore, we explore the capabilities of its successor, StyleGAN3, which boasts enhanced image generation, facilitating smooth and realistic transitions. By comparing the performance of StyleGAN3 on public dataset, we aim to establish the most efficient generative model for this purpose. Evaluations were conducted using the SIFT (Scale-Invariant Feature Transform) algorithm into our evaluation framework. Preliminary findings suggest that StyleGAN3 offers superior generative capabilities, enhancing equivariance in synthetic palmprint generation.

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Section: Datasetmentioning

confidence: 99%