A Hybrid DWT PCA and ICA Features for Face Recognition using ANN
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1
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN
DE HC NW
ISBN: 9783330008052 bzw. 3330008059, in Deutsch, Lap Lambert Academic Publishing, gebundenes Buch, neu.
Lieferung aus: Deutschland, Versandkostenfrei innerhalb von Deutschland.
Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database. Lieferzeit 1-2 Werktage.
Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database. Lieferzeit 1-2 Werktage.
2
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN
DE PB NW
ISBN: 9783330008052 bzw. 3330008059, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN: Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database. Englisch, Taschenbuch.
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN: Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database. Englisch, Taschenbuch.
3
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN
DE NW
ISBN: 9783330008052 bzw. 3330008059, in Deutsch, neu.
Lieferung aus: Vereinigtes Königreich Grossbritannien und Nordirland, Lieferzeit: 11 Tage, zzgl. Versandkosten.
Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database.
Face recognition plays an important role in biometrics base personal identification. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, and control of access to security areas and so on. The proposed method is based on Principal Component Analysis (PCA) of image with a combination of details of DWT. This approach reduces the storage requirement and computation time while preserving the data. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. Neural Network and K-NN Classifier are used to classify the features and the similarity measure is done by Euclidian Distance. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithm. The approach PCA-DWT-ICA-hybrid is evaluated on MATLAB using Yale face database.
5
A Hybrid DWT, PCA and ICA Features for Face Recognition using ANN
DE PB NW
ISBN: 3330008059 bzw. 9783330008052, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
6
A Hybrid DWT PCA and ICA Features for Face Recognition using ANN
~EN PB NW
ISBN: 3330008059 bzw. 9783330008052, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
Hybrid DWT, PCA and ICA Features for Face Recogni (2017)
DE PB NW
ISBN: 9783330008052 bzw. 3330008059, in Deutsch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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