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- W4386827590 abstract "Despite simultaneously ignoring the intensity distribution that is formed by the finger tissue and, in some instances, processing it as background noise, the majority of finger vein feature extraction algorithms achieve satisfactory performance due to their ability to represent texture. This project makes use of two- directional two-dimensional Fisher Principal Component Analysis, also known as (2D) 2 FPCA, for feature extraction. This type of noise is presented as a novel soft biometric trait for improving finger vein recognition performance. In order to demonstrate that the intensity distribution that is formed by the finger tissue in the background can be extracted as a soft biometric trait for recognition, a comprehensive analysis of the finger vein imaging principle and the characteristics of the image are first presented." @default.
- W4386827590 created "2023-09-19" @default.
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- W4386827590 date "2023-07-31" @default.
- W4386827590 modified "2023-09-26" @default.
- W4386827590 title "Raspberry PI-Based Finger Vein Recognition System Using PCA NET" @default.
- W4386827590 doi "https://doi.org/10.26562/irjcs.2023.v1006.24" @default.
- W4386827590 hasPublicationYear "2023" @default.
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