Journal of the Operations Research Society of China ›› 2022, Vol. 10 ›› Issue (4): 849-860.doi: 10.1007/s40305-020-00332-7

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Automatic Identification Fingerprint Based on Machine Learning Method

Long The Nguyen1, Huong Thu Nguyen2,3, Alexander Diomidovich Afanasiev1, Tao Van Nguyen3   

  1. 1 Laboratory of Artificial Intelligence and Machine Learning, Institute of Information Technology and Data Science, Irkutsk National Research Technical University, Irkutsk, Russia;
    2 Baikal School of BRICS, Irkutsk National Research Technical University, Irkutsk, Russia;
    3 University of Information and Communication Technology, Thai Nguyen University, Thai Nguyen, Viet Nam
  • Received:2019-09-23 Revised:2020-03-04 Online:2022-12-30 Published:2022-11-09
  • Contact: Long The Nguyen,Huong Thu Nguyen,Alexander Diomidovich Afanasiev,Tao Van Nguyen E-mail:thelongit88@gmail.com;thuhuongyb@gmail.com;aad@istu.edu;nvtao@ictu.edu.vn
  • Supported by:
    This research was supported by the National Natural Science Foundation of China (Nos. 00001 and 00010) and Chongqing Municipal Education Commission (No. KJ120616).

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.

Key words: Fingerprint identification, Feature extraction, Image segmentation, Wavelet transform, Neural network algorithm, Machine learning

CLC Number: