FACE RECOGNITION OFFICE SECURITY SYSTEM USING LAB VIEW 8.6

Facial recognition (or face recognition) is a type of biometric software application that can identify a specific individual in a digital image by analyzing and comparing patterns. Facial recognition systems are commonly used for security purposes but are increasingly being used in a variety of other applications. In this context, nodal points are end points used to measure variables of a person‘s face, such as the length or width of the nose, the depth of the eye sockets and the shape of the cheekbones. These systems work by capturing data for nodal points on a digital image of an individual‘s face and storing the resulting data as a face print. The face print can then be used as a basis for comparison with data captured from faces in an image or video. This paper presents a novel face detection approach in color images. We employ spatial histograms as robust features for face detection. The spatial histograms consist of marginal distribution of color image information. Facial texture and shape are preserved by the spatial histogram representation. A hierarchical classifier combining histogram matching and support vector machine is utilized to identify face and non-face. The experiments show that this approach performs an excellent capability for face detection, and it is robust to lighting changes.