%0 Conference Paper %B Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on %D 2005 %T Handwriting matching and its application to handwriting synthesis %A Yefeng Zheng %A David Doermann %K (artificial %K deformation %K deformation; %K handwriting %K image %K intelligence); %K learning %K learning; %K matching; %K point %K recognition; %K sampling; %K SHAPE %K synthesis; %X 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. %B Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on %P 861 - 865 Vol. 2 - 861 - 865 Vol. 2 %8 2005/09/01/aug %G eng %R 10.1109/ICDAR.2005.122