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Data-driven Handwriting Synthesis with Conjoined Manner
Date Issued
2014
Date
2014
Author(s)
Lin, Tse-Ju
Abstract
A person''s handwriting appears differently within a typical range of variations, and the shapes of handwriting characters also show complex interaction with their nearby neighbours. This makes automatic synthesis of handwriting characters and paragraphs very challenging. In this paper, we propose a method for synthesizing handwriting texts according to a writer''s handwriting style. The synthesis algorithm is composed by two phases. First, we create the shape models for different characters based on one writer''s data. Then, we compute the cursive probability to decide whether each pair of neighbouring characters are conjoined together or not. By jointly modelling the handwriting style and conjoined property through a novel trajectory optimization, final handwriting words can be synthesized from a set of collected samples. Furthermore, the paragraphs'' layouts are also automatically generated and adjusted according to the writer''s style obtained from the same dataset. We demonstrate that our method can successfully synthesize an entire paragraph that imitate a writer''s handwriting using his/her collected handwriting samples.
Subjects
影像生成
應用
Type
thesis
File(s)
No Thumbnail Available
Name
ntu-103-R01922004-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):cfaede94701d09d82e313131f375156f