Automatic Recognition and Repair System of Mural Image Cracks Based on Cloud Edge Computing and Digitization

Abstract

Mural painting is the art on the wall, it is the painting that people draw on the wall, it is one of the earliest forms of painting in human history, and it is also an accessory part of the building. The decorative and beautifying functions of murals make them an important aspect of environmental art. Cloud edge computing is a combination of cloud computing and edge computing, that fully absorbs the advantages of both cloud computing and edge computing and maximizes their advantages. In this study, based on cloud edge computing and digital technology, the automatic identification and repair system of fresco image cracks is studied. Image segmentation techniques have been proposed in this study, using 60 murals in three regions as experimental objects. Through experimental analysis, it is found that the traditional pine poise treatment method takes the shortest repair time. However, for a specific image, it is difficult to guarantee the quality of its restoration. The mural image in area A was repaired with the conventional pine pitch repair method, which took 113.01 seconds, and the subjective evaluation was 69 points. Using the repair method described in this study to repair, it takes 127.38 seconds, and its subjective evaluation score is the highest, which is 87 points. The experimental results have shown that the cloud edge computing method and digital technology have had a certain positive effect on the identification and repair system of fresco image cracks.