This paper proposes an off-line text-independent writer identification method applicable to Japanese and Korean sentences. It is assumed that the writer of a writing in question exists in a certain group of people and that reference writings written by each person in the group can be used for identification. In the proposed method, relative frequencies of some model patterns are counted on the binary pattern of each writing and are used as the feature to measure the distance between two writings. Based on a modified Mahalanobis' distance for this feature, the person whose reference writing is nearest to the writing in question is judged as the writer. The effectiveness of the proposed method is examined through an experiment using Japanese and Korean writings. Error rates in the experiment were different depending on conditions such as volume of reference writings, dimension of adopted features, and number of people to be identified. In some cases, error rates as low as 0% were observed. Error rates tend to be lower in Korean writings probably because Hangul is composed of a smaller number of letters compared to Kanji and Hiragana in Japanese writing.