This paper aims to describe a computational algorithm for automatic recognition of vehicle registration plate from recorded video. There is extensive research and literature on different ways to implement automatic recognition of vehicle registration plate. Popular methods involve the use of technologies like computer vision, image precession, artificial neural networks and fuzzy logic systems. Some of these have been implemented, but none so far have been able to guarantee high levels of accuracy. Also, most of these systems work on still images captured from a camera. In this approach, we begin by obtaining frames having image of moving car from the video using motion detection. The region containing the number plate is then identified by the Canny edge detection algorithm and Hough transformation. Segmentation of the plate is then undertaken, using histogram analysis, to obtain the separate characters. Neural techniques are then applied to recognize the individual characters. With further work on the components of such a system and their successful integration, a largely automated system can be developed for traffic and law enforcement purposes. The deployment of such a system in different states or countries carries with it its own unique issues, and there is a need to configure the system to properly function in the required domain..