In this paper the structural properties of alphabetic and digital characters on vehicle license plate are analyzed in detail and three types of feature are extracted for their recognition. These features include (a) global ones

i.e. closed curve in character

which can be used for character coarse classification; (b) minutiae

which are some key points in thinned image such as endings

bifurcations and crossings of strokes and can be used for character precise classification

(c) corners in strokes which can be used to discriminate similar characters. Algorithms for fast detection of closed curve based on theory of graph and minutiae and for corner finding based on external contour lines of binary image are also discussed. The recognition rate of alphabetic and digit character of the system based on these structural features is approximate to 96% and the time for feature extraction and character recognition is about 20ms/character. This shows that the proposed structural features have good discriminating power of similar characters and can be used for the fast classification and recognition of characters on vehicle license plate.