Face Recognition By Using Nearest Feature Midpoint Algorithm
Good facial recognition system is a system which can handle variation that arise when making a face image. These variation can include facial expressions, accessories that are used, the level of illumination and direction of image acquisition. Variation will be captured by the virtual lines are made of at least two prototypes in a class. The virtual line will generalize the variation that may occur on the second prototype. Face identification process will be done by finding the shortest distance between the face that will be recognized by all the Variation result of extrapolation and interpolation prototype in each class. Implementation of this method can achieve accuracy rates of more than 90% to the execution time of 0.5 seconds under optimal condition.