Real Time Face Recognition Using Minimum Measurements when at Least Two Thirds of the Face is Present in the Image

A real time face recognition architecture using minimum number of face-measurements is presented in this paper. The measurements that we have taken are – neck width, eyebrow width, distance between eyebrow and eyeball, eyeball width, amount of black points in the eyebrow and eyeball regions and amount of forehead. In this paper we have presented an algorithm which is able to recognize faces with different expressions for moving persons when horizontally at least two thirds of the face is present on the image-frame. There are no color measurements in this method because color measurements some times greatly depend on the operating systems, graphical resolutions etc and cause problems in face recognition. The measurements that we have taken are expression invariant. For a training face these measurements are determined and stored and recognition is performed based on the weighted sum of errors of these measurements. This method is faster than most of the existing methods and it has a high recognition rate.