Biometric Detection Technique for Fingerprint Recognition Using Minutiae Detection
DOI:
https://doi.org/10.51903/pixel.v17i1.2000Keywords:
Fingerprint, Feature Extraction, Minutiae, BiometricAbstract
Fingerprint recognition is a popular biometric technology due to its unique properties and high accuracy rate. Fingerprint recognition systems generally use fingerprint image representations, such as grayscale images, phase images, skeleton images, and minutiae. In this research, fingerprint image pre-processing is performed using Gaussian Blur, Median Blur, Thresholding, Otsu Thresholding, Thinning with Guo-Hall algorithm, and Minutiae Detection. Minutiae detection produces 426 termination points and 459 bifurcation points. The results of the pre-processing and minutiae detection were then used for minutiae matching on 5 different images. Minutiae matching produces varying degrees of similarity with a high level of accuracy, reaching an average accuracy of 88.80%.
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[4] A. Rungchokanun, K. Srisutheenon, and V. Areekul, “Minutiae Selection using Reference Point for Fingerprint Data Interoperability and Identification,” in 2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), IEEE, Jun. 2020, pp. 439–442. doi: 10.1109/ECTI-CON49241.2020.9158325.
[5] N. Zaeri, “Minutiae-based Fingerprint Extraction and Recognition,” in Biometrics, InTech, 2011. doi: 10.5772/17527.
[6] Z. BIAN, D. ZHANG, and W. SHU, “KNOWLEDGE-BASED FINGERPRINT POST PROCESSING,” Intern J Pattern Recognit Artif Intell, vol. 16, no. 01, pp. 53–67, Feb. 2002, doi: 10.1142/S021800140200154X.
[7] N. Ahmed and A. Varol, “Minutiae based partial fingerprint registration and matching method,” in 2018 6th International Symposium on Digital Forensic and Security (ISDFS), IEEE, Mar. 2018, pp. 1–5. doi: 10.1109/ISDFS.2018.8355343.
[8] P. Singh and L. Kaur, “Fingerprint feature extraction using morphological operations,” in 2015 International Conference on Advances in Computer Engineering and Applications, IEEE, Mar. 2015, pp. 764–767. doi: 10.1109/ICACEA.2015.7164805.
[9] P. Mishra, A. K. Shrivastava, and A. Saxena, “Enhanced Thinning Based Finger Print Recognition,” International Journal on Cybernetics & Informatics, vol. 2, no. 2, pp. 33–46, Apr. 2013, doi: 10.5121/ijci.2013.2204.
[10] V. Espinosa-Duro, “Minutiae detection algorithm for fingerprint recognition,” IEEE Aerospace and Electronic Systems Magazine, vol. 17, no. 3, pp. 7–10, Mar. 2002, doi: 10.1109/62.990347.
[11] A. I. Khan and M. A. Wani, “Strategy to extract reliable minutia points for fingerprint recognition,” in 2014 IEEE International Advance Computing Conference (IACC), IEEE, Feb. 2014, pp. 1071–1075. doi: 10.1109/IAdCC.2014.6779474.
[12] A. I. Khan and M. A. Wani, “Strategy to extract reliable minutia points for fingerprint recognition,” in 2014 IEEE International Advance Computing Conference (IACC), IEEE, Feb. 2014, pp. 1071–1075. doi: 10.1109/IAdCC.2014.6779474.
[13] R. M. Yusof and N. Sulaiman, “Postprocessing algorithm for security features extraction,” in 2012 International Conference on E-Learning and E- Technologies in Education (ICEEE), IEEE, Sep. 2012,pp. 219–222. doi: 10.1109/ICeLeTE.2012.6333392.
[14] R. P. Krish, J. Fierrez, D. Ramos, F. Alonso- Fernandez, and J. Bigun, “Improving automated latent fingerprint identification using extended minutia types,” Information Fusion, vol. 50, pp. 9–19, Oct. 2019, doi: 10.1016/j.inffus.2018.10.001.
[15] S. Albalawi, L. Alshahrani, N. Albalawi, R. Kilabi, and A. Alhakamy, “A Comprehensive Overview on Biometric Authentication Systems using Artificial Intelligence Techniques,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 4, 2022, doi:10.14569/IJACSA.2022.0130491.
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Published
2024-07-26
How to Cite
Pontoh, F. J. (2024). Biometric Detection Technique for Fingerprint Recognition Using Minutiae Detection. Pixel :Jurnal Ilmiah Komputer Grafis, 17(1), 193–200. https://doi.org/10.51903/pixel.v17i1.2000
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