Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3169 2018 2018 College of Science for Women, University of Babylon, Iraq Faqeda Faqeda College of Science for Women, University of Babylon, Iraq Mohammed Abdullah Naser Face detection is important in computer vision and image processing, particularly in surveillance, security systems, video analytics, and facial recognition applications. However, face detection algorithms face challenges like position variations, lighting fluctuations, size and resolution differences, facial expressions, and background clutter. This research aims to develop a system that achieves high accuracy in detecting and localizing faces using local descriptors and spatial feature extraction techniques, specifically the Histogram of Oriented Gradients method (HOG). Using videos from the YouTube Face database, features were extracted from frames and trained using a convolutional neural network (CNN). The HOG technique achieved a 94% accuracy rate and good localization compared to CNN without feature extraction. 2025 2025 229 237 10.54216/FPA.170117 https://www.americaspg.com/articleinfo/3/show/3169