Abstract For a number of decades, a great deal of researches has been undertaken in the study of pattern recognition in order to recognise human features such as face, hand, mouth and eyes recognitions. NEURAL Network is an efficient technique for providing a good if not the best solutions to certain types of problems such as where the data examples contain lots of attributes and where the rules which govern the problem are not clearly understood. Therefore, using Neural Network applications are widely spread across the world. For instance, in industrial process control, target marketing, sales forecasting, recovery of a telecommunication from faulty software and facial recognition. This project concerned with digital image processing using MATLAB and utilising BackPropagation Neural Network algorithm for classifying human features recognition especially eyes. Human feature recognition under varying illumination remains a challenging problem. However, the results of a number of experiments was carried out, the findings confirm the technique of Back-Propagation algorithm was capable of distinguish the eyes from non-eyes in different situations. Much progress has been made toward creating methods that can deals with the data set in values in order to obtain the optimum BackPropagation Neural Network architecture.