Abstract This paper describes hybrid access control system based on a new approach face recognition and PIN code identification, which is done by finding the closest match between features implemented on the same databases. This approach involves of two subsystems identification and matching, and the output from these subsystems are combined to decide final output, that authorizes the access to the secure building for only certain persons while denying the access for the others. Identification involves comparing an existing image against a large image database in order to identify the individual depicted. In verification, a biometric identifier is compared to another template through a PIN number of database. For this purpose, a camera is set in the door looking at the inter and the captured frames are analyzed. The implementation includes neural networks for PIN code identifications, and analysis starts by selecting the regions of interest in the face images using NN. This paper present a neural network based upright frontal face recognition approach. The algorithm of face recognition is implemented using preprocessing of face image and two-stage neural network. The first net finds the eyes region of a person and improving image by histogram equalization. The second uses an image of the area around eyes region to identify the person. Using arbitration between multiple networks with rarely overlap in region images to clean up the results significantly improves the accuracy of the recognition. A feasibility investigation and evaluation for face recognition based solely on new concept is conducted which covers all conditions of human face recognition under varying lighting condition, varying facial expression, and varying pose. The proposed system structure is implemented as a software package using C++ and Visual Basic. With newly proposed methods, allowing fast processing and accurate recognition. .
أ د خميس عواد زيدان | Khamis A. Zidan | 10870