摘要
In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.
In the Chinese character intelligent formation system without Chinese character library, it is possible that the same basic element in different Chinese characters is different in position, size and shape. The geometry transformation from basic elements to the components of Chinese characters can be realized by affine transformation, the transformation knowledge acquisition is the premise of Chinese character intelligent formation. A novel algorithm is proposed to ac-quire the affine transformation knowledge of basic elements automatically in this paper. The interested region of Chi-nese character image is determined by the structure of the Chinese character. Scale invariant and location invariant of basic element and Chinese character image are extracted with SIFT features, the matching points of the two images are determined according to the principle of Minimum Euclidean distance of eigenvectors. Using corner points as identifi-cation features, calculating the one-way Hausdorff distance between corner points as the similarity measurement from the affine image to the Chinese character sub-image, affine coefficients are determined by optimal similarity. 70244 Chinese characters in National Standards GB18030-2005 character set are taken as the experimental object, all the characters are performed and the experimental courses and results are presented in this paper.
