COMPUTATIONAL APPROACHES TO DOCUMENTING ENDANGERED TRADITIONAL PAINTING PRACTICES

Abstract

Traditional painting styles are important in terms of cultural identity, cultural heritage and knowledge transmission in the community. Now, though, in the digital age, those arts are vanishing as the number of digital design tools grows and digital visual materials are no longer in such short supply that their values are being undermined; tastes are changing and younger people have less affinity for handcrafted work. We discuss in this paper the documentation of traditional painting styles with the help of computer assisted techniques, more specifically the way digital technologies can help to document, classify, compare and conserve hand-made artistic practice in the long term. The research highlights the need for image processing, machine learning, digital archiving and pattern recognition to enable them to analyze their visual elements such as color composition, brushstroke texture, motif structure, and stylistic variation. The results indicate that by using computer-assisted techniques, endangered painting traditions may be retained through making them accessible in digital form, assisting artists and researchers, and raising awareness of the dangers and disappearance of art skills. In the meantime, the paper says that technology can't replace the skill of humans, but it is an assisting arm in cultural preservation. This study not only provides valuable insights for safeguarding traditional handcrafted painting styles but also supports the creation of sustainable solutions for the digital era.