  Scene text recognition plays an important role in many computer vision
applications. The small size of available public available scene text datasets
is the main challenge when training a text recognition CNN model. In this
paper, we propose a CNN based Chinese text recognition algorithm. To enlarge
the dataset for training the CNN model, we design a synthetic data engine for
Chinese scene character generation, which generates representative character
images according to the fonts use frequency of Chinese texts. As the Chinese
text is more complex, the English text recognition CNN architecture is modified
for Chinese text. To ensure the small size nature character dataset and the
large size artificial character dataset are comparable in training, the CNN
model are trained progressively. The proposed Chinese text recognition
algorithm is evaluated with two Chinese text datasets. The algorithm achieves
better recognize accuracy compared to the baseline methods.
