TY - GEN
T1 - Handwriting matching and its application to handwriting synthesis
AU - Zheng, Yefeng
AU - Doermann, David
PY - 2005
Y1 - 2005
N2 - Since it is extremely expensive to collect a large volume of handwriting samples, synthesized data are often used to enlarge the training set. We argue that, in order to generate good handwriting samples, a synthesis algorithm should learn the shape deformation characteristics of handwriting from real samples. In this paper, we present a point matching algorithm to learn the deformation, and apply it to handwriting synthesis. Preliminary experiments show the advantages of our approach.
AB - Since it is extremely expensive to collect a large volume of handwriting samples, synthesized data are often used to enlarge the training set. We argue that, in order to generate good handwriting samples, a synthesis algorithm should learn the shape deformation characteristics of handwriting from real samples. In this paper, we present a point matching algorithm to learn the deformation, and apply it to handwriting synthesis. Preliminary experiments show the advantages of our approach.
UR - https://www.scopus.com/pages/publications/33947425620
U2 - 10.1109/ICDAR.2005.122
DO - 10.1109/ICDAR.2005.122
M3 - Conference contribution
SN - 0769524206
SN - 9780769524207
T3 - Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
SP - 861
EP - 865
BT - Proceedings of the Eighth International Conference on Document Analysis and Recognition
T2 - 8th International Conference on Document Analysis and Recognition
Y2 - 31 August 2005 through 1 September 2005
ER -