Face recognition system is very beneficial in real-time applications, concentrated in security control systems. Face Detection and Recognition is a vital area in the province of validation. In this project, the Open CV based face recognition strategy has been proposed. This model integrates a camera that captures an input image, an algorithm - Haar Cascade Algorithm for detecting face from an input image, identifying the face and marking the attendance in an excel sheet. The proposed system implements features such as detection of faces, extraction of the features, exposure of extracted features, analysis of students' attendance, and monthly attendance report generation. Faces are recognized using advanced LBP using the database that contains images of students and is used to identify students using the captured image. Better precision is accomplished in results and the system takes into account the changes that occurs in the face over some time.
Face Recognition, Haarcascades, Adaboost, OpenCv, LBPH
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