Face Recognition using Fast GA

Abstract

Face Identification System using a fast genetic algorithm computation (FGA) is presented. FGA is used to compute and search the face in a database. The objective of the work is to make a face identification system which can recognize face from a given image or any other image streaming system like webcam. The system also has to detect the face from a system accurately in order to identify the face accurately. The image can be captured either from a proposed webcam or a captured JPEG or PNG image or any other data source. The system needs training with adequate sample images to perform this operation. Training the generic system plays a vital role in identifying the face in an image. A tolerance is identified as a limit to the genetic algorithm which acts as a terminal condition to the evolution. A unique encoding is used which stores the facial features of a human face into numeric string which can be stored and searched with much ease thereby decreasing the search and computational time. Template matching technique is applied to identify the face in a big picture. Generation of an Eigen face is obtained by the stage a mathematical practice called PCA. Eigen Features is also computed such that the measurement of facial metrics is done using nodal point measurement.