@article{Tran_Phạm Văn Trường_2022, title={Personal Verification Based on Finger Knuckle Print Pecognition System Using Raspberry Pi}, volume={3}, url={https://mca-journal.org/index.php/mca/article/view/81}, abstractNote={<p><span class="fontstyle0">This paper proposes an approach for personal verification based on<br />finger knuckle recognition (FKR) system using Raspberry Pi 4 and<br />Pi camera. We evaluate and compare some advanced methods for<br />biometric feature extraction and matching in terms of recognition<br />accuracy and computational time. From the evaluation and analysis,<br />we found that the Binary Orientation Cooccurrence Vector<br />(BOCV)-which is previously often used for palmprint recognition,<br />is the method of choice for our low-cost and real time FKR system.<br />Along with evaluating our data, we also assess some recent methods on the Hong Kong Polytechnic University Contactless Finger<br />Knuckle Images Database. Experiments show that the BOCV<br />method obtains the accuracy over 90% and offers realtime recognition.</span></p>}, number={1}, journal={Measurement, Control, and Automation}, author={Tran, Thi-Thao and Phạm Văn Trường}, year={2022}, month={Jun.}, pages={60-64} }