Human Face Recognition Using Combination of ZCA Feature Extraction method and Deep Neural Network

2019 ◽  
Author(s):  
Naing Min Tun ◽  
Alexander I. Gavrilov ◽  
Pyae Phyo Paing
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Face Recognition ◽  
Extraction Method ◽  
Deep Neural Network ◽  
Human Face ◽  
Human Face Recognition ◽  
Feature Extraction Method

A NEURAL BASED HUMAN FACE RECOGNITION SYSTEM USING AN EFFICIENT FEATURE EXTRACTION METHOD WITH PSEUDO ZERNIKE MOMENT

2002 ◽  
Vol 11 (03) ◽  
pp. 283-304 ◽  
Author(s):  
JAVAD HADDADNIA ◽  
KARIM FAEZ ◽  
MAJID AHMADI
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Extraction Method ◽  
Rbf Neural Network ◽  
Zernike Moment ◽  
Human Face ◽  
Shape Information ◽  
Feature Extraction Method ◽  
Face Features ◽  
Face Localization

This paper introduces an efficient method for the recognition of human faces in 2D digital images using a feature extraction technique that combines the global and local information in frontal view of facial images. The proposed feature extraction includes human face localization derived from the shape information. Efficient parameters are defined to eliminate irrelevant data while Pseudo Zernike Moments (PZM) with a new moment orders selection method is introduced as face features. The proposed method while yields better recognition rate, also reduces the classifier complexity. This paper also examines application of various feature domains as face features using the face localization method. These include Principle Component Analysis (PCA) and Discrete Cosine Transform (DCT). The Radial Basis Function (RBF) neural network has been used as the classifier and we have shown that the proposed feature extraction method requires an RBF neural network classifier with a simpler structure and faster training phase that is less sensitive to select training and testing images. Simulation results on the Olivetti Research Laboratory (ORL) database and comparison with other techniques indicate the effectiveness of the proposed method.

scholarly journals Deep Neural Network for Human Face Recognition

2018 ◽  
Vol 8 (1) ◽  
pp. 63-71 ◽  
Author(s):  
Priya Gupta ◽  
◽  
Nidhi Saxena ◽  
Meetika Sharma ◽  
Jagriti Tripathi
Keyword(s):  
Neural Network ◽  
Face Recognition ◽  
Deep Neural Network ◽  
Human Face ◽  
Human Face Recognition

scholarly journals A Wavelet Scattering Feature Extraction Approach for Deep Neural Network Based Indoor Fingerprinting Localization

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1790 ◽  
Author(s):  
Bedionita Soro ◽  
Chaewoo Lee
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Extraction Method ◽  
Deep Neural Network ◽  
Small Deformation ◽  
Rotation Invariant ◽  
Feature Extraction Method ◽  
Path Coefficients ◽  
Scattering Transform ◽  
Artificial Neural Network Ann

The performance of an Artificial Neural Network (ANN)-based algorithm is subject to the way the feature data is extracted. This is a common issue when applying the ANN to indoor fingerprinting-based localization where the signal is unstable. To date, there is not adequate feature extraction method that can significantly mitigate the influence of the receiver signal strength indicator (RSSI) variation that degrades the performance of the ANN-based indoor fingerprinting algorithm. In this work, a wavelet scattering transform is used to extract reliable features that are stable to small deformation and rotation invariant. The extracted features are used by a deep neural network (DNN) model to predict the location. The zeroth and the first layer of decomposition coefficients were used as features data by concatenating different scattering path coefficients. The proposed algorithm has been validated on real measurements and has achieved good performance. The experimentation results demonstrate that the proposed feature extraction method is stable to the RSSI variation.

F-2DCCA: A New Fuzzy Feature Extraction Method for Face Recognition

2013 ◽  
Vol 12 (4) ◽  
pp. 823-828
Author(s):  
Yanyan Liu ◽  
Yibin Zhao ◽  
Jianguo Wang
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Extraction Method ◽  
Feature Extraction Method
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