Deep learning-driven palmprint and finger knuckle pattern-based multimodal Person recognition system

نویسندگان

چکیده

Biometric recognition systems are widely being used in several applications due to its distinctiveness and reliability. In recent years, hand-based person has received much momentum stability, feature richness, reliability higher user acceptability. this paper, we propose a multimodal hand biometric system based on Finger Knuckle Print (FKP) Palmprint. particular, the PCANet deep learning method is employed extract distinctive features from each modality. Then, multiclass SVM utilized compute matching score for individual Finally, level fusion performed combine scores via different rules such as, min, sum, max multiplication. The performance of proposed evaluated publicly available database known as PolyU. First, conducted experiments single FKP Palmprint traits. Next, were performed. framework was able achieve 0.00% EER (equal error rates) 100% rank-1 performance. addition, with outperformed existing methods.

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ژورنال

عنوان ژورنال: Multimedia Tools and Applications

سال: 2022

ISSN: ['1380-7501', '1573-7721']

DOI: https://doi.org/10.1007/s11042-022-12384-3