Applying DWT and PC with Artificial Neural Network for FACE RECOGNITION

Benkaddou Mohammed Kamel

Article Details

Applying DWT and PC with Artificial Neural Network for FACE RECOGNITION

Authors:

Benkaddou Mohammed Kamel

Publisher:

Université de Ghardaia

Journal:

مجلة الواحات للبحوث و الدراسات Vol.7 Issue 2, pp.7-13

Document Type:

Article

Publication Date:

12/2014

Document Language:

English

Document ID (Org No.):

2001444934

pISSN:

2588-1892

Keywords:

Abstract:

 This manuscript presents, Face
recognition by combining different extraction
approaches combining PCA (principal Component
Analysis), DWT (Discrete wavelet transform
neural networks. This method consists of four
steps: i) Preprocessing, ii) Dimension reduction
using DWT, iii) feature extraction using PCA and
iv) classification using neural network. To validate
this work, we have tested this technique on frontal
images of the ORL and Yale databases.
Keywords -.

Article Details

Applying DWT and PC with Artificial Neural Network for FACE RECOGNITION

Authors:

Benkaddou Mohammed Kamel

Publisher:

Université de Ghardaia

Journal:

مجلة الواحات للبحوث و الدراسات Vol.7 Issue 2, pp.7-13

Document Type:

Article

Publication Date:

12/2014

Document Language:

English

Document ID (Org No.):

2001444934

pISSN:

2588-1892

Face Recognition

Biometrics

PCA

Neural Networks

Feature extraction

eigenfaces DWT

Issues

Article Details

Applying DWT and PC with Artificial Neural Network for FACE RECOGNITION

Authors: Benkaddou Mohammed Kamel

Publisher: Université de Ghardaia

Journal: مجلة الواحات للبحوث و الدراسات Vol.7 Issue 2, pp.7-13

Document Type: Article

Publication Date: 12/2014

Document Language: English

Document ID (Org No.): 2001444934

pISSN: 2588-1892

Face Recognition

Biometrics

PCA

Neural Networks

Feature extraction

eigenfaces DWT

Issues

Authors:

Benkaddou Mohammed Kamel

Publisher:

Université de Ghardaia

Journal:

مجلة الواحات للبحوث و الدراسات Vol.7 Issue 2, pp.7-13

Document Type:

Article

Publication Date:

12/2014

Document Language:

English

Document ID (Org No.):

2001444934

pISSN:

2588-1892