Personal Verification Based on Finger Knuckle Print Pecognition System Using Raspberry Pi

Authors

  • Thi-Thao Tran Hanoi University of Science and Technology
  • Pham Van Truong Hanoi University of Science and Technology

Keywords:

Nhận dạng khớp ngón tay, Định danh người, Raspberry PI, Sinh trắc học, BOCV

Abstract

This paper proposes an approach for personal verification based on
finger knuckle recognition (FKR) system using Raspberry Pi 4 and
Pi camera. We evaluate and compare some advanced methods for
biometric feature extraction and matching in terms of recognition
accuracy and computational time. From the evaluation and analysis,
we found that the Binary Orientation Cooccurrence Vector
(BOCV)-which is previously often used for palmprint recognition,
is the method of choice for our low-cost and real time FKR system.
Along with evaluating our data, we also assess some recent methods on the Hong Kong Polytechnic University Contactless Finger
Knuckle Images Database. Experiments show that the BOCV
method obtains the accuracy over 90% and offers realtime recognition.

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Published

2022-06-06

How to Cite

Tran, T.-T., & Phạm Văn Trường. (2022). Personal Verification Based on Finger Knuckle Print Pecognition System Using Raspberry Pi. Measurement, Control, and Automation, 3(1), 60-64. Retrieved from https://mca-journal.org/index.php/mca/article/view/81