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Most vehicle head faces have one window, two illuminative lamps and a license plate, a method is proposed using features about them to detect vehicle head face. Edges of window are straight lines commonly, in the projection histogram whose direction is not parallel to window edge, there is an abrupt change at the edge location. This property can be used to locate window candidate position. If lamps and license plate have all been located, the candidate is verified surely and truly. In order to recognize vehicle type, a hybrid neural network is designed to analyze the extracted features. The network contains two parts, the 1st part uses support vector machines, the 2nd part contains four perceptrons which verifies the output of 1st and produces recognized result. Synthetic experiment of this method is given and some discussions have also been made.