Open AccessMobile APP fingerprint feature extraction pattern recognition based on Random Game
Author(s) -
J. Morris Chang,
Xingtao Zuo,
Botao Hou,
Shuo Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1792/1/012003
Subject(s) - pattern recognition (psychology) , fingerprint (computing) , artificial intelligence , feature extraction , computer science , fingerprint recognition , feature (linguistics) , k nearest neighbors algorithm , signature recognition , image (mathematics) , computer vision , philosophy , linguistics
The traditional feature extraction method for pattern recognition increases the computational complexity of the recognition method due to the excessive feature extraction, which leads to the low accuracy of the recognition method. To solve the above problems, a fingerprint feature extraction pattern recognition method based on random game is proposed for mobile APP. After the fingerprint image processing, the fingerprint features in the image are extracted. After removing the pseudo-feature points from the extracted image features, the pattern recognition of fingerprint features is completed by using the stochastic game theory. Through the simulation experiment, it is verified that the recognition accuracy of the proposed method increases by about 1/5, and has better recognition stability.