Abstract
In this paper we present a novel algorithms for face and character recognition using combination of wavelet transforms and principal component analysis (PCA). At first, face features are extracted using combination of Haar and Daubechies wavelet transform. Then obtained features are used for face recognition by PCA (eigenfaces). In the case of character recognition we use combination of wavelet transform and principal component analysis for character feature extraction. Then obtained extracted features are classified using multi-layer feed-forward neural networks. For each training character we use one neural network, which determines the confidence whether an input character is its prototype or not. The proposed algorithms give an effective performance of face and character recognition on noisy images and compete with state-of-the-art algorithms.
| Original language | English |
|---|---|
| Title of host publication | 2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Print) | 9781479971022 |
| DOIs | |
| Publication status | Published - 1 Jul 2015 |
| Event | 2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Omsk, Russian Federation Duration: 21 May 2015 → 23 May 2015 |
Other
| Other | 2015 International Siberian Conference on Control and Communications, SIBCON 2015 |
|---|---|
| Country | Russian Federation |
| City | Omsk |
| Period | 21.5.15 → 23.5.15 |
Fingerprint
Keywords
- character recognition
- face recognition
- neural networks
- principal component analysis
- wavelet transforms
ASJC Scopus subject areas
- Computer Networks and Communications
- Control and Systems Engineering
Cite this
Development of algorithms for face and character recognition based on wavelet transforms, PCA and neural networks. / Bui, T. T T; Phan, N. H.; Spitsyn, V. G.; Bolotova, Yu A.; Savitsky, Yu V.
2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. 7147224.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Development of algorithms for face and character recognition based on wavelet transforms, PCA and neural networks
AU - Bui, T. T T
AU - Phan, N. H.
AU - Spitsyn, V. G.
AU - Bolotova, Yu A.
AU - Savitsky, Yu V.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - In this paper we present a novel algorithms for face and character recognition using combination of wavelet transforms and principal component analysis (PCA). At first, face features are extracted using combination of Haar and Daubechies wavelet transform. Then obtained features are used for face recognition by PCA (eigenfaces). In the case of character recognition we use combination of wavelet transform and principal component analysis for character feature extraction. Then obtained extracted features are classified using multi-layer feed-forward neural networks. For each training character we use one neural network, which determines the confidence whether an input character is its prototype or not. The proposed algorithms give an effective performance of face and character recognition on noisy images and compete with state-of-the-art algorithms.
AB - In this paper we present a novel algorithms for face and character recognition using combination of wavelet transforms and principal component analysis (PCA). At first, face features are extracted using combination of Haar and Daubechies wavelet transform. Then obtained features are used for face recognition by PCA (eigenfaces). In the case of character recognition we use combination of wavelet transform and principal component analysis for character feature extraction. Then obtained extracted features are classified using multi-layer feed-forward neural networks. For each training character we use one neural network, which determines the confidence whether an input character is its prototype or not. The proposed algorithms give an effective performance of face and character recognition on noisy images and compete with state-of-the-art algorithms.
KW - character recognition
KW - face recognition
KW - neural networks
KW - principal component analysis
KW - wavelet transforms
UR - http://www.scopus.com/inward/record.url?scp=84941063882&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941063882&partnerID=8YFLogxK
U2 - 10.1109/SIBCON.2015.7147224
DO - 10.1109/SIBCON.2015.7147224
M3 - Conference contribution
AN - SCOPUS:84941063882
SN - 9781479971022
BT - 2015 International Siberian Conference on Control and Communications, SIBCON 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -