@conference {13563, title = {Handwriting matching and its application to handwriting synthesis}, booktitle = {Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on}, year = {2005}, month = {2005/09/01/aug}, pages = {861 - 865 Vol. 2 - 861 - 865 Vol. 2}, abstract = {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.}, keywords = {(artificial, deformation, deformation;, handwriting, image, intelligence);, learning, learning;, matching;, point, recognition;, sampling;, SHAPE, synthesis;}, doi = {10.1109/ICDAR.2005.122}, author = {Yefeng Zheng and David Doermann} }