Abstract
This paper experimented with the combination of the Haar-Cascade Classifier and Local Binary Pattern Histogram in creating a Face Recognition System using Python programming language. Images were gathered using Python script from the 10persons selected while facing the camera. Each individual had 1000 photos that were used to train a model. Another Python script was created for training, identification and recognition. The overall efficiency rating of the model was 84% which denotes a practical recommendation for utilization. The findings of this study contribute as a reference for further development of face recognition with other image classification algorithms
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