Multimodal Biometrics Fusion Algorithm Using Deep Reinforcement Learning

Quan Huang and Xiaofeng Li

Mathematical Problems in Engineering, 2022, vol. 2022, 1-9

Abstract: Multimodal biometrics fusion plays an important role in the field of biometrics. Therefore, this paper presents a multimodal biometrics fusion algorithm using deep reinforcement learning. In order to reduce the influence of user behavior, user’s personal characteristics, and environmental light on image data quality, data preprocessing is realized through data transformation and single-mode biometric image region segmentation. A two-dimensional Gobar filter was used to analyze the texture of local sub-blocks, qualitatively describe the similarity between the filter and the sub-blocks and extract the phase information and local amplitude information of multimodal biometrics features. Deep reinforcement learning was used to construct the classifier of different modal biometrics, and the weighted sum fusion of different modal biometrics was implemented by fractional information. The multimodal biometrics fusion algorithm was designed. The Casia-iris-interval-v4 and NFBS datasets were used to test the performance of the proposed algorithm. The results show that the fused image quality is better, the feature extraction accuracy is between 84% and 93%, the average accuracy of feature classification is 97%, the multimodal biometric classification time is only 110 ms, the multimodal biometric fusion time is only 550 ms, the effect is good, and the practicability is strong.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/8544591.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/8544591.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8544591

DOI: 10.1155/2022/8544591

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().