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
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.