ID identification by using face detection and recognition systems

In recent years, significant achievements have been achieved in the field of face recognition. Face recognition are special pattern recognition which are used in banking for identity approving and the entrance of controlled areas, the places where the security control impending to airports, to control machines, to follow-up of persons. In this study, face recognition applications on the Yale face databases have been performed by using PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), LBP (Local Binary Patterns). Database consist of right-light, center-light, left-right, no glasses, glasses, normal, wink, sleepy, surprised, happy, sad images. In the face recognition pre-processing steps, HE (Histogram Equalization), HE+ Median Filter, HE+Gaussian filter, He+Laplace Filter was used. It is provided to select the appropriate method from the system depending on state of image. Thus the system recognition rate increases of up to 6% was observed. Application was developed by using Microsoft Visual Studio 2010 C #. EMGU CV library for image processing algorithms and SQL Server 2008 Express for database processing were used.