Face Recognition to Identify Look-Alike Faces using Support Vector Machine

Face recognition has been one of the most interesting technology to study for many researchers. It allows a huge number of face images to be recognized in just a short amount of times, rather than recognizing each image individually through a normal human's eyes. Its idea is generally based on the assumption that each individual has a unique identity that can be distinguished between one another. However, in the real world, there are individuals who have similar faces to each other. They are referred as "look-alike" faces. This research was conducted to recognize look alike faces. Each image is represented by the features it contains. The classification method used in this research was Support Vector Machine, with the implementation of kernel. Two types of kernel used in this research were the Radial Basis Function kernel and the polynomial kernel. Results showed that SVM with Radial Basis Function kernel obtained higher accuracies.