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Human face recognition is one of the most challenging topics in the areas of pattern recognition, image processing and computer vision. Before recognizing the human face, it is necessary to detect a face then extract the face features. Many methods have been created and developed in order to perform face detection and two of the most popular methods are Haar Cascade Classifiers and Histogram of Oriented Gradients (HOG), which have a very low rate of false negative. This paper presents a comparison of the two methods in terms of precision, recall, f-1 score and accuracy using confusion matrix