Research on Thangka Edge Detection Technology Based on Deep Learning
Thangkas are an integral part of Tibetan Buddhist culture,with intricate,detailed patterns and varied,co-lourful symbols.Thangkas are mostly painted on canvases such as silk with natural mineral pigments,which are then framed in silk and satin for preservation.However,with the passage of time,this preservation method is easily affect-ed by external factors such as erosion,which can lead to varying degrees of damage.In order to avoid the damage of this important intangible cultural heritage,a convolutional neural network architecture(CNN)-based edge detection model DMSCNN is proposed,which can accurately capture the complex feature information in the Thangka image and output the intact edge image.In addition,this paper compares the DMSCNN model with the Canny operator and other multi-scale deep learning models,and the results show that the model has better results than other methods on Tangka images.This study not only provides a guarantee for the protection,research and inheritance of Thangka pic-tures,but also provides a useful example of the application of deep learning in the field of cultural heritage protection.Future research will focus on improving the model and attempting to extend it to other conservation efforts.
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