Abstract
The fingerprint identification technology has been developed and applied effectively to security systems in financial transactions, personal information security, national security, and other fields. In this paper, we proposed the development of a fingerprint identification system based on image processing methods that clarify fingerprint contours, using machine learning methods to increase processing speed and increase the accuracy of the fingerprint identification process. The identification system consists of the following main steps: improving image quality and image segmentation to identify the fingerprint area, extracting features, and matching the database. The accuracy of the system reached 97.75% on the mixed high- and low-quality fingerprint database.
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Acknowledgements
The authors are grateful to ICO’2018 Pattaya, Thailand, and ICO’2019 Koh Samui, Thailand, for giving them opportunity to present the research results in this special issue. This research was performed at Irkutsk National Research Technical University Irkutsk, Russia.
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This research was supported by the National Natural Science Foundation of China (Nos. 00001 and 00010) and Chongqing Municipal Education Commission (No. KJ120616).
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Nguyen, L.T., Nguyen, H.T., Afanasiev, A.D. et al. Automatic Identification Fingerprint Based on Machine Learning Method. J. Oper. Res. Soc. China 10, 849–860 (2022). https://doi.org/10.1007/s40305-020-00332-7
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DOI: https://doi.org/10.1007/s40305-020-00332-7
Keywords
- Fingerprint identification
- Feature extraction
- Image segmentation
- Wavelet transform
- Neural network algorithm
- Machine learning