Recover drawing orders from a Chinese handwriting image
is a challenge issue. Most of English drawing order recovery(
DOR) methods perform unsatisfactorily in Chinese. This
paper proposes a novel image-to-sequence algorithm to deal
with Chinese DOR problem. The proposed method utilizes
two regression convolution neural network(CNN) models to
generate two corresponding pen-tip movement heat-maps. To
estimate pen-tip movement for most of the normal states in
writing process, the algorithm analyzes the above two heatmaps
with a specifically designed framework. Then the drawing
order is restored through a simple iteration process based
on the proposed framework. Experiments on public online
handwriting database show that our method have got a remarkable
result for Chinese DOR tasks. In addition, for English
tasks, our method performs superiorly among state-ofthe-
art methods.
; Yang, Minghao
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