Device Synchronization Using A Computerize Face Detection And Recognition System For Cybersecurity
Keywords:
AdaBoost Algorithm, Haar, cascade, Face detection and recognition system (FRDS)Abstract
Face recognition system is an application for identifying someone from image or videos. Face recognition is classified into three stages i.e. Face detection, Feature Extraction, Face Recognition. Face detection is an application for detecting object, analyzing the face, understanding the localization of the face and face recognition. It is used in many application for new communication interface, security etc. The face detection algorithm converts the input images from a camera to binary pattern and transverse the face location of candidates using the AdaBoost Algorithm. AdaBoost Algorithm selects the best set of Haar features and implement it in cascade to decrease the detection time. Face recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. The accuracy is not a major problem that specifies the performance of automatic face recognition system alone, the time factor is also considered a major factor in real time environments. Recent architecture of the computer system can be employed to solve the time problem, this architecture represented by multi-core CPUs and many-core GPUs that provide the possibility to perform various tasks by parallel processing.
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