A comprehensive automatic labeling and repair strategy for cracks and peeling conditions of literary murals in ancient buildings

Article type: Research Article

Authors: Du, Pei^{; *}

Affiliations: Art institute of Sichuan University, Chengdu, China

Correspondence: [*] Corresponding author. Pei Du, Art institute of Sichuan University, Chengdu 610000, China. E-mail: [email protected].

Abstract: To protect the historical and cultural heritage, the application of self-organizing mapping networks and genetic algorithms in the restoration of ancient architectural murals is studied. The results show that the average repair time for different types of mural paintings is less than 60 seconds, and the shortest repair time is only 17.81 seconds. The evaluation effect of the research model is good, and the comprehensive efficiency evaluation of the mural restoration work is improved by about 40.42%. The repair system has excellent performance, and the algorithm has high feasibility and effectiveness. The impact of restoring murals is substantial, and the extent of restoration is highly consequential for the restoration of ancient architectural murals.

Keywords: Ancient architectural murals, self-organizing networks, genetic algorithms, automatic annotation, restoration strategies

DOI: 10.3233/JIFS-235769

Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3557-3568, 2024