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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%.

For reliable face identification, the fusion process of multi-spectral vision features produces robust classification systems, this paper exploits the power of thermal facial image invariant moments features fused with the visible facial image invariant moments features to propose a new multi-spectral hybrid invariant moment fusion system for face identification. And employs Feed-forward neural network to train the moments' features and make decisions. The evaluation system uses databases of visible thermal pairs face images CARL and UTK-IRIS databases and gives an accuracy reaches 99%.

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Designing a multi-biometric system for safe access to buildings is a very critical process because this system will act as an alternative of humans in observation, and must make smart decisions to protect the building from any intruder depending on the biometric information of the entering persons. In this paper a full design of a proposed multi-biometric system will be presented, two sensors are used (Visible and Thermal). the proposed system consists of several subsystems The first is the construction of a database that contains all the photos and information about each person who belongs to the building, the central system using visible and thermal cameras, and the peripheral system using visible cameras only. The central system is capable of remotely identifying and ensure of the health condition (Temperature, Heart Rate, Respiration Rate) of each entering person which is a very important process, especially with the COVID-19 pandemic. The peripheral system monitors any suspicious issue like crowed or walking outside allowed lines.