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• W3153243847 abstract "Robust facial feature extraction is an effective and important process for face recognition and identification system. The facial features should be invariant to scaling, translation, illumination and rotation, several feature extraction techniques may be used to increase the recognition accuracy. This paper inspects three-moment invariants techniques and then determines how is influenced by the variation which may happen to the various shapes of the face (globally and locally) Globally means the whole face shapes and locally means face part's shape (right eye, left eye, mouth, and nose). The proposed technique is tested using CARL database images. The proposal method of the new method that collects the robust features of each method is trained by a feed-forward neural network. The result has been improved and achieved an accuracy of 99.29%." @default.
• W3153243847 created "2021-04-26" @default.
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• W3153243847 date "2021-03-25" @default.
• W3153243847 modified "2023-10-03" @default.
• W3153243847 title "A New Hybrid Technique for Face Identification Based on Facial Parts Moments Descriptors" @default.
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• W3153243847 doi "https://doi.org/10.30684/etj.v39i1b.1903" @default.
• W3153243847 hasPublicationYear "2021" @default.
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