Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
933-938,960

Research on lightweight recognition algorithm based on key features of finger vein and AdaFace loss

Liu Runji
Wang Yiding
School of Information, North China University of Technology, Beijing 100144, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0304

Abstract

Finger vein recognition methods based on deep learning usually require a large amount of computing resources, it limits their promotion and popularization on embedded devices. The adoption of lightweight network faces the problem of decreasing accuracy due to the reduction of model parameters. Therefore, this paper proposed a lightweight recognition algorithm based on key features of finger vein and AdaFace loss. In the MicroNet network framework, firstly, this paper proposed FMixconv convolution to replace the deep convolution in the original network, which could obtain multi-scale information of vein features while reducing parameters. Secondly, the method used a lightweight attention module, CA module, to focus on key information of venous characteristics from space and channel. Finally, the algorithm added AdaFace loss into the loss function, through the characteristics of the norm to evaluate image quality, to reduce the impact of image quality degradation on training. The recognition accuracy of the proposed algorithm on SDUMLA-HMT, FV-USM and self-built datasets reached 99.84%, 99.39% and 99.42%, while the number of parameters was only 0.82 M. Experimental results show that the proposed network is ahead of other methods in accuracy and parameter size.

Foundation Support

国家自然科学基金资助项目(62276018)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0304
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Technology of Graphic & Image
Pages: 933-938,960
Serial Number: 1001-3695(2024)03-044-0933-06

Publish History

[2023-09-06] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

刘润基, 王一丁. 基于静脉关键特征和AdaFace损失的轻量级指静脉识别算法 [J]. 计算机应用研究, 2024, 41 (3): 933-938,960. (Liu Runji, Wang Yiding. Research on lightweight recognition algorithm based on key features of finger vein and AdaFace loss [J]. Application Research of Computers, 2024, 41 (3): 933-938,960. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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