Abstract
Face recognition technology has many uses in the distribution of photographs, from detecting persons in pictures to automatically grouping pictures based on people's faces. Several methods have been proposed for face detection, including deep learning methods like Convolutional Neural Networks and Histogram of Oriented Gradients. This study analyzes the suitability of CNN and HOG algorithms for recognizing faces with higher accuracy and speed. The accuracy of the algorithms implemented and the standard of quality of the images determine how well face recognition technology performs in the distribution of photographs. Further, this study also contributes to present effectiveness and impact on storing and retrieving images as well as its advantages and disadvantages in the context of image distribution applications.