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Summary In view of the problem that the traditional face recognition algorithm cannot be effectively applied to the identification of mobile payment, a lightweight improvement scheme of the dynamic heteroscedasticity based on the classical scale transformation algorithm is proposed, which can automatically study and adaptively add the reliable test samples to the training sample space, with reasonable division and scientific weight distribution characteristics, so that the scheme can improve both the recognition rate and running time. The improved algorithm is tested in the ORL face database and Yale face database, respectively, with the recognition rate improved by 6.13% and 14.11%, and the operating efficiency increased by 9.1% and 4.7%, respectively, compared with the classic scale transformation algorithm. The recognition rate in the ORL face database has achieved 74.05%, with significant improvement compared with PCA, LBP, and other classic algorithms. And the mobile payment scheme is implemented in Android smart phones. The experimental data has verified the feasibility of the improved algorithm in the Android system. Finally, an improved scheme based on the cloud architecture is proposed.
Meiyan Du (Fri,) studied this question.