The invention provides a fast document type recognition method based on full-sized feature extraction. The method comprises the following steps of document image preprocessing, including image zooming, graying and noise filtering; document image feature extraction, including Hessian matrix building, scale space generation, primary determination of feature points, precise positioning of the feature points, main direction determination of selected feature points, feature point descriptor construction and feature value string generation; document image feature value comparison, including document similarity calculation and comparison algorithm optimization. According to the method, an image is preprocessed through software, and additional hardware equipment does not need to be added. According to the method, the scale-invariant feature is creatively introduced for improving a typical SURF feature extraction algorithm, so that the problem of matching failure due to error amplification of the SURF algorithm caused by scale variations is fundamentally solved. The method has the advantage that a multi-thread technology and a large cache are used for solving the problems of large data volume calculation during comparison and the harsh time requirement of a user on an electronic government affair platform.