Calligraphy's Reflective Expression: Intelligent Chinese Calligraphy Affective and Style Recognition

Calligraphy expresses people's inner mood and reflects their self-cultivation. Style and emotion plays a key role in calligraphy artistry. Consequently, we applied intelligent technology to analyze the emotion and artistic style recognition of Chinese calligraphy artworks. A dataset of 5,000 calligraphy images was established, including art works over seventy renowned Chinese calligraphists. We compared several deep-learning methods to build the best model. The results show that the optimal model achieves an accuracy of 0.9319 with MobileNet in calligraphy emotion recognition, while it achieves the best accuracy of 0.972 in calligraphy font style recognition, and the highest classification accuracy of 0.943 in calligraphy artist's style recognition respectively using ResNet50. Finally, an intelligent Chinese calligraphy emotion and style exploration application are developed based on the optimal model.