Car identification is a goal in traffic control, transport planning, travel time measurement, managing parking lot traffic and so on. Most car identification algorithms contain a standalone plate segmentation process followed by a plate contents reading. A pyramidal algorithm for license plate segmentation, looking for textured regions, has been developed on a PC based system running Unix. It can be used directly in applications not requiring real time. When input images are relatively small, real-time performance is in fact accomplished by the algorithm. When using large images, porting the algorithm to special digital signal processors can easily lead to preserving real-time performance. Experimental results, for stationary and moving cars in outdoor scenes, showed high accuracy and high scores in detecting the plate. The algorithm also deals with cases where many character strings are present in the image, and not only the one corresponding to the plate. This is done by the means of a constrained texture regions classification.