Human Ear Fusion Recognition Algorithm Based on Sparse Representation
ZHENG Qiumei
MA Maodong
WANG Fenghua
SUN Yanxiang
LI Bo
Abstract：A single biometrics has certain limitations in the identification process. This paper proposes a biometric fusion algo?rithm for human ear based on the correlation between human ear and human ear. In this paper,principal component analysis(PCA) is used to extract features of human face and human ear,and then sparse representation is used to classify the extracted features. The sparse representation based face recognition method has achieved good results in the case of occlusion and noise. Experimental results show that the recognition algorithm based on sparse representation of human ear fusion has better recognition accuracy.
Keywords：sparse representationprincipal component analysismultiple biometricsfeature fusion
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1640-1643,1661 )