Abstract
Chinese characters have been created into many font styles, such as official script, running script, and regular script. Other than that, some famous calligraphers, such as Ouyang Xun and Yan Zhenqing, have produced fonts with their style. Being able to detect and recognize these font styles quickly and accurately has essential applications in graphic design, page layout, handwriting identification, and other use cases. Distinguishing between font styles requires professional knowledge, which almost inevitably leads to errors for unprofessional people. Therefore, this paper presents a sword-like model based on a convolutional neural network with a sword structure to recognize font styles for Chinese characters. This model includes 15 convolutional layers. For each layer, we gradually increase the number of convolutional kernels to better extract the classification features of the input image. This paper uses four downsampling layers in the model. For each downsampling operation, the length and width of the image become half of their original values while the number of channels gradually increases, leading to a sword-like shape. As a result, we name our model as SwordNet. We also created a Chinese font dataset called the Nankai Chinese Font Style dataset and made it available on Github. Using the above dataset, we compared the accuracy of our model with six other state-of-the-art network models. The experiments showed that SwordNet could achieve an average recognition accuracy of 99.03% in multiple experiments, while the other six models can only achieve accuracy up to 94.91%. So we can conclude that SwordNet could perform better in font style recognition than other models.
Highlights
During the long history of Chinese characters, a diverse set of font styles have been developed, such as Cursive Script, Clerical Script, and Small Seal Script
NANKAI CHINESE FONT STYLE DATASET we described the details of our dataset: Nankai Chinese Font Style (NCFS) dataset [25]
SwordNet obtained 99.03% accuracy on the 18 class NCFS dataset
Summary
During the long history of Chinese characters, a diverse set of font styles have been developed, such as Cursive Script, Clerical Script, and Small Seal Script. X. Li et al.: SwordNet: Chinese Character Font Style Recognition Network design and build neural network models which can provide high accuracy. To classify the font style of a Chinese character in an image, one first needs to extract features from that image, and the features are used to train the model or for classification. The selection of the features has a great impact on recognition accuracy As a result, this method has poor generalizability. Given an image containing a Chinese character, SwordNet can recognize the font style of Chinese characters in the image end-to-end without complicated data pre-processing or human intervention. To test the generalizability of SwordNet, we collected ten common font styles and six ancient Chinese calligraphic works, including Shuowen Xiaozhuan, with a total of 18 different font styles.
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