1. A method for recognizing a handwritten character, comprising the following steps of A. creating a coarse classification template composed of first sample centers of character classes and a fine classification template composed of second sample centers of the character classes, wherein the fine classification template is obtained by using an eigen transformation matrix to perform eigen transformation on samples of the character classes; B. receiving a handwritten character input signal from a user and gathering a discrete coordinate sequence of trajectory points of an inputted character corresponding to the handwritten character input signal, and pre-processing the discrete coordinate sequence to obtain a normalized coordinate sequence of the inputted character; C. extracting eigenvalues according to the normalized coordinate sequence and decomposing vector line sections formed by all adjacent trajectory points into eight standard directions to calculate a multi-dimensional eigenvector of the inputted character; D. selecting a part of the eigenvalues from the multi-dimensional eigenvector of the inputted character, matching the inputted character with the coarse classification template to select a plurality of the most similar sample centers from the coarse classification template, and using character classes corresponding to the plurality of sample centers as candidate character classes; and E. using the eigen transformation matrix in the step A to perform eigen transformation on the multi-dimensional eigenvector of the inputted character, selecting sample centers of the candidate character classes obtained in the step D from the fine classification template for matching with the eigen-transformed inputted character respectively, and determining the most similar character classes among the candidate character classes for the user to select.