1. A method for character recognition based on a Gabor filter group, said method comprising: (a) pre-processing a character image, said pre-processing including receiving, pre-processing the character image of a character to be recognized, and obtaining a binary or gray image with N×N pixels for each character to be recognized, wherein said binary or gray image for each character to be recognized is represented by a matrix &lsqb;A(i, j)&rsqb; N×N ; (b) processing the matrix &lsqb;A(i, j)&rsqb; N×N for the character image of each character to be recognized obtained in the step (a), said processing including: extracting stroke direction information of the character to be recognized, said extracting including employing the Gabor filter group which is composed of K two-dimension Gabor filters to extract stroke information in K different directions from the matrix &lsqb;A(i, j)&rsqb; N×N of the character image of the character to be recognized, and obtaining K matrixes &lsqb;G m (i, j)&rsqb;M×M, m&equals;1... K, of the character image of the character to be recognized, wherein each of said matrixes &lsqb;G m (i, j)&rsqb; M×M, m&equals; 1... K, possesses M×M pixels and represents the stroke information of one of the K directions; extracting features from blocks, including extracting features from the blocks in said K matrixes &lsqb;G m (i, j)&rsqb; M×M, m&equals; 1... K, of the image of the character to be recognized, and obtaining an initial recognition feature vector V with a high dimension of the character image of the character to be recognized; compressing the features, including compressing the initial recognition feature vector V and obtaining a recognition feature vector V c with a low dimension of the character image of the character to be recognized; recognizing the character, including employing a specific classifier to calculate a distance between the recognition feature vector Vc and a category center vector of each character category, selecting a nearest distance from distances and the character category corresponding to the nearest distance, and calculating a character code of the character to be recognized according to a national standard code of the character category; and (c) repeating step (b) to obtain each character code of each character image.