Abstract
In recent years, with the development of three-dimensional digitization of cultural relics, most cultural relic protection units have a large number of fine three-dimensional data of cultural relics, especially complex geometric objects such as painted cultural relics. At present, how to automatically extract surface disease information from the fine three-dimensional color model of painted cultural relics and avoid the accuracy loss caused by reducing the dimension by conventional methods is an urgent problem to be solved in the investigation of cultural relics diseases.In view of the above problems, this paper proposes an automatic and high-precision extraction method for cultural relics surface shedding diseases based on three-dimensional fine data. Firstly, this paper designs a two-dimensional and three-dimensional integrated data conversion model based on OSG three-dimensional engine, which realizes the mutual conversion between three-dimensional color model texture and two-dimensional image. Secondly, a SLIC segmentation algorithm with adaptive K value is proposed, which solves the problem of superpixel K value setting and improves the accuracy of image segmentation. Finally, through the two-dimensional and three-dimensional integrated model, the disease is statistically analyzed and labeled on the three-dimensional model.Experiments show that for painted plastic objects with complex surfaces, the disease extraction method based on three-dimensional fine model proposed in this paper has improved geometric accuracy compared with the current popular orthophoto extraction method, and the disease investigation is more comprehensive ; compared with the current three-dimensional manual extraction method in commercial software, this method greatly improves the efficiency of disease extraction while ensuring the extraction accuracy. The research method of this paper activates a large number of existing three-dimensional fine data of cultural protection units, and converts data mining and analysis from conventional two-dimensional data to three-dimensional data, which is more in line with the scientific utilization of data in accuracy and efficiency, and has certain scientific research value, leading value and practical significance.