Implementasi Pengenalan Wajah Dengan Metode HOG Untuk Pencatatan Kehadiran Mahasiswa Pada Campus Event
Abstract
Face recognition is one of the identification systems developed based on differences in facial features of a person who has high accuracy. Currently the Campus Event committee at Nurtanio University is still using manual notes to write the attendance list of students who take part in the activities mentioned above. After observing this, the author is interested in building an application to record attendance using facial recognition. The software development in this research uses the waterfall method with the stages of requirement definition, system design, and implementation. The diagram design uses BPMN (Business Process Model and Notation) and UML (Unified Modeling Language). The programming language used is Python, OpenCV as image processing and Histogram Of Oriented Gradients (HOG) for face recognition algorithm which has been simplified into a face_recognition library. Software testing with black box method. With this study, attendance recording can be done by recognizing the participants' faces, thereby increasing efficiency and reducing queues
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