This document proposes a methodology for recognizing facial expressions with increased speed and accuracy. It involves detecting faces, preprocessing images through greyscaling and contrast adjustment, extracting features through local binary patterns, and classifying expressions. The proposed system includes face detection using Haar classifiers, image processing steps, feature detection by analyzing distances between action points on facial characteristics, and using a classifier to output the expression. Future work involves testing this approach against other methods using specialized datasets and hardware to develop a faster and more reliable facial expression recognition system.