Most systems are intelligent and the industrial world is moving now towards
technology. Most industrial systems are now computerized and offer a high speed.
However, Face recognition is a biometric system that can identify people from their
faces. For few number of people to be identified, it can be considered as a fast
system. When the number of people grew to be bigger, the system cannot be adopted
in a real-time application because its speed will degrade along with its accuracy.
However, the accuracy can be enhanced using pre-processing techniques but the
time delay is still a challenge. A series of experiments had been done on AT&TORL
database images using Enhanced Face Recognition System (EFRS) that is

Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap