• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Multimodal Fusion Method Based on a Rotation Invariant Hierarchical Model for Finger-based Recognition

Vol. 15, No. 1, January 31, 2021
10.3837/tiis.2021.01.008, Download Paper (Free):

Abstract

Multimodal biometric-based recognition has been an active topic because of its higher convenience in recent years. Due to high user convenience of finger, finger-based personal identification has been widely used in practice. Hence, taking Finger-Print (FP), Finger-Vein (FV) and Finger-Knuckle-Print (FKP) as the ingredients of characteristic, their feature representation were helpful for improving the universality and reliability in identification. To usefully fuse the multimodal finger-features together, a new robust representation algorithm was proposed based on hierarchical model. Firstly, to obtain more robust features, the feature maps were obtained by Gabor magnitude feature coding and then described by Local Binary Pattern (LBP). Secondly, the LGBP-based feature maps were processed hierarchically in bottom-up mode by variable rectangle and circle granules, respectively. Finally, the intension of each granule was represented by Local-invariant Gray Features (LGFs) and called Hierarchical Local-Gabor-based Gray Invariant Features (HLGGIFs). Experiment results revealed that the proposed algorithm is capable of improving rotation variation of finger-pose, and achieving lower Equal Error Rate (EER) in our homemade database.


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Cite this article

[IEEE Style]
Z. Zhong, W. Gao and M. Wang, "A Multimodal Fusion Method Based on a Rotation Invariant Hierarchical Model for Finger-based Recognition," KSII Transactions on Internet and Information Systems, vol. 15, no. 1, pp. 131-146, 2021. DOI: 10.3837/tiis.2021.01.008.

[ACM Style]
Zhen Zhong, Wanlin Gao, and Minjuan Wang. 2021. A Multimodal Fusion Method Based on a Rotation Invariant Hierarchical Model for Finger-based Recognition. KSII Transactions on Internet and Information Systems, 15, 1, (2021), 131-146. DOI: 10.3837/tiis.2021.01.008.