The Application of a Face Recognition System For a Personal face Database

Abstract

This study aimed to apply face recognition of the personal face detection, which this system implemented Eigenface to analyze face details in facial comparison database. Eigenface is an approach in the theory of principal component analysis (PCA). It was accepted that facial images could be synthesized based on data from the model and can store a person’s face parameters in a small set of numbers, which is accurate and reliable. The data used in the assessment of effi ciency and developed software, including 30 images. It was divided into three groups, and each group contained ten images. The experimental results were shown as follows ; the fi rst dataset contained ten images with an image resolution of 100x100 pixels. We achieved a precision of 90%. The second dataset also contained ten images with an image resolution of 150x150 pixels. The result showed that we achieved a precision of 80%. The third dataset included ten images with a resolution of 200x200 pixels. We achieved a precision of only 70%. Our proposed system achieved a mean precision of 80% and was considered as good efficiency. It can be applied for application in criminal face detection.

Keywords

• face recognition
• face detection
• principal component analysis
• eigenface