When recognizing handwritten characters, normalization of characters has been usually done prior to feature extraction. Some authors point out that improvement of normalization increases the recognition rate. Thus, normalization techniques must be carefully examined. We have proposed a Gabor filter-based handwritten character recognition system. Our main interest is to select the best normalization technique for Gabor filters. We conduct comparative experiments and show that position, slant, and thickness normalization is best, with regard to minimizing the error.