Proposed Method for Face Image Recognition Using Spectral Eigenvector Algorithms

Abstract

Facial recognition systems are computer-based security systems that are able to automatically detect and identify human faces. Biometric systems Though Iris Scan, Finger Print and Hand Geometry biometric system have proven to be effective, it requires cooperation from the person being scanned, the last are critical in a wide range of applications such as banking system, E-commerce, smart cards, and access control to secure system, face recognition system is one of the most reliable biometric systems, which is used for identifying persons. The proposed system describes a method for human recognition based on eigenface, correlation distance, training set of images, and a threshold which it used to classify the images and accept the detection of images that have a minimum value below the threshold. And noise removal used to enhance the performance of the original PCA algorithm in the recognition process; it gives more accurate results in recognition. This study aim is to design a face image recognition system, which is capable of identifying a face with high level of accuracy. Therefore, this system can be applied to a wide range of many applications.