This thesis develops an algorithm for automatic number plate recognition (ANPR) and implemented it on the Beagle Board. It is an image processing technology which uses number plate to identify the vehicle. The objective is to design an efficient automatic authorized vehicle identification system by using the vehicle number plate. It can be used to implement on the entrance for security control of a highly restricted area like military zones or area around top government offices e.g. Parliament, Supreme Court etc. The algorithm developed here is aimed to be lightweight so that it can be run in real time. With images provided by a USB web camera the system will be able to recognize the number plate under normal condition. The algorithm is built in three sections; the first is the initial detection of a number plate using edge and intensity features in the image; in the second, the text of the number plate is found; last is the actual character recognition. Optical character recognition technique is used for the character recognition. The resulting data is then used to compare with the records on a database. The major advantages of the system is its real-time capability and that it does not require any additional sensor input (e.g. from infrared sensors) except a video stream. The system is implemented and simulated in Matlab, and its performance is tested on real image. It is observed that the developed system successfully detects and recognize the vehicle number plate on real images.