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Experiment result shows the significance of the proposed structure over other networks in both font and style classification. In this paper, four kinds of styles belonging to standard font are classified with a novel CNN structure where two squeeze-and-excitation modules that emphasize informative feature maps and suppress useless features are embedded after convolution layers, and a Haar transform layer that fuses the features is imposed before softmax layer. However, most of the studies focus on the classification of five basic fonts that is somewhat different from styles. Traditional feature operators have some drawbacks that leave room for modern methods like convolutional neural network (CNN). The automatic recognition of the styles of calligraphy by image processing techniques has important meaning in arts collection and auction, etc. It is liked by many people, and our mission is to endeavor to pursue calligraphy and make contributions to the business with technical means. Chinese calligraphy is a valuable cultural heritage belonging to the world.

Chinese calligraphy style font