Nowadays people use keys, security cards, password or pattern to open the door. The aim of this paper is to help people for improvement of the door security of sensitive locations by using face detection and recognition. Face is a complex multidimensional structure and needs enhanced computing techniques for detection and recognition. This paper comprises of three subsystems: namely face detection, face recognition and automatic door access control. Image acquisition is the process of capturing an image. The face is detected by using the Viola Jones method and face recognition is implemented by using the Principal Component Analysis (PCA). Face Recognition based on PCA is generally referred to as the use of Eigen faces. If a face is recognized, it is authenticated, vice-versa. The door will open automatically for the authenticated person due to the command of the microcontroller. Since PCA reduces the dimensions of face images without losing important features, facial images for many persons can be stored in the database. Although many training images are used, computational efficiency cannot be decreased significantly. Therefore, face recognition using PCA can be more useful for door security system than other face recognition schemes. Keywords—Viola-Jones face detection method, PCA, Eigenvector, Covariance, Euclidean distance, Eigen face, microcontroller.