Chinese Calligraphy Character Image Recognition and Its Applications in Web and Wechat Applet Platform

Abstract

Calligraphy is an important part of traditional Chinese culture. Authentic calligraphy works are usually preserved on paper, bamboo slips and stone tablets, which are easy to be destroyed and not easily appreciated by most calligraphy lovers anytime and anywhere. Therefore, in order to facilitate the preservation and appreciation of calligraphy works, digital technology and computer technology are used for digital storage, management and service. The time complexity of image recognition algorithm based on traditional method is relatively high, especially the algorithm based on feature matching has low tolerance to Chinese character deformation. Therefore, this paper tries to use deep learning to study the image recognition of Chinese characters. However, some existing data sets of calligraphic images have a small number of corresponding images, which cannot support deep learning network training. In view of this problem, a data augmentation method based on character glyph and stroke characteristics is proposed. This method starts from two aspects of Chinese character glyph and stroke. Chinese character glyph is changed by affine changes of the restricted conditions. The stroke information of Chinese characters is extracted by super pixel and the stroke information is changed to expand the diversity of Chinese characters in the data set. In the process of character recognition, mixup data augmentation algorithm is combined with Inception v4 network which has excellent performance in Imagenet classification tasks?for network recognition training to improve network generalization ability. Experiments show that the algorithm proposed in this paper based on deep learning has a higher recognition effect than previous algorithms, especially in cursive and running recognition. The digital calligraphy knowledge service system based on web terminal and WeChat small program terminal is designed and implemented, which can provide the digital calligraphy knowledge service of calligraphy work segmentation and calligraphy character recognition.