[1]JIN Yifan,WANG Haitao,JIA Wei.Using palmprint lines for data enhancement of palmprint recognition based on deep learning[J].CAAI Transactions on Intelligent Systems,2024,19(5):1178-1189.[doi:10.11992/tis.202308026]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
19
Number of periods:
2024 5
Page number:
1178-1189
Column:
学术论文—机器感知与模式识别
Public date:
2024-09-05
- Title:
-
Using palmprint lines for data enhancement of palmprint recognition based on deep learning
- Author(s):
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JIN Yifan; WANG Haitao; JIA Wei
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School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China
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- Keywords:
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biometric identification; deep learning; personal authentication; Gabor filter; palmprint recognition; palm line extraction; data enhancement; convolutional neural network
- CLC:
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TP391.4
- DOI:
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10.11992/tis.202308026
- Abstract:
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In recent years, palmprint recognition technology has attracted growing attention. However, complex application scenarios bring difficulties in the process of palmprint recognition. Data enhancement plays an important role in palmprint recognition algorithms based on deep learning. Owing to the uniqueness of palmprint, nearly all the feature data it contains lie within the palmprint lines. As a result, traditional global data enhancement methods have little effect in this case. In this study, a data enhancement method based on palmprint lines is proposed. In the method, a multi-stage palmprint line extraction algorithm is first proposed on the basis of the traditional image processing method. Subsequently, a data enhancement scheme on palmprint recognition is designed on the basis of the extracted palmprint lines. Experiments demonstrate that applying this data enhancement method to improve palmprint images has achieved better results than four widely used deep-learning models. The data enhancement method is simple and efficient and can play a role in actual applications.