Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine
[1]Chen Tiejun,Cai Jinshou,Guo Li.Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine[J].Journal of Zhengzhou University (Engineering Science),2016,37(02):37-41.[doi:10.3969/j.issn.1671-6833.201505016]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
37
Number of periods:
2016 02
Page number:
37-41
Column:
Public date:
2016-04-18
- Title:
- Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine
- Keywords:
- curvelet transform; B2DPCA; voting; ELM; face recognition
- CLC:
- -
- Abstract:
- Aiming at the defect that wavelet analysis cannot make full use of the unique geometric features of the data itself when dealing with multi-dimensional graphics, the second generation of curvelet transform (SGCT) method is used to process face images, and the image with the largest standard deviation is selected. Scale layer coefficients are used to complete the feature extraction of face images, and combined with data dimensionality reduction based on bidirectional two-dimensional principal component analysis (B2DPCA), a hybrid voting mechanism-based extreme learning machine (voting Extreme learning machine, VELM) face recognition algorithm. By comparing with the classification results of other algorithms, it is proved that the algorithm has a higher recognition accuracy.
- References:
- -
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