Country of origin estimation from composite faces using Kernel Principal Compenent Analysis

In this work, an algorithm is introduced that classifies test images into their originated countries using composite faces generated according to different countries. Also aim to increase success rate at implementation process using three color channel (R-G-B), color feature vector and local standard deviation matrix. Algorithm used Kernel Principal Component Analysis with gauss kernel structure for dimension reduction process. And optimal component number for dimension reduction process is determined via Horn´s parallel analysis method. At the end of process these obtained features are classified via Multi Support Vector Machines.