Digital extraction and segmentation of intangible cultural heritage paper-cut patterns.

As a unique intangible cultural heritage in Chinese traditional culture, paper-cut art is now facing the dilemma of inheritance and development, and with the death of paper-cut artists and the damage and loss of paper-cut works, some paper-cut types also disappear. Therefore, the digital protection...

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Publicado en:Digital Scholarship in the Humanities Vol. 41; no. 1; pp. 41 - 51
Autores principales: Chen, Daoling, Cheng, Pengpeng
Formato: Artículo
Publicado: Oxford University Press / USA Apr2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2026
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        10.1093/llc/fqaf006
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        atl: Digital extraction and segmentation of intangible cultural heritage paper-cut patterns.
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          Chen, Daoling
          Cheng, Pengpeng
        affil:
          College of Fashion and Art Engineering, Minjiang University, Fuzhou, 350108, China
          School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, 311199, China
      su:
        Paper arts
        Image segmentation
        Edge detection (Image processing)
        Feature extraction
        Cultural policy
        Genetic algorithms
      sug:
        subj:
          Paper arts
          Image segmentation
          Edge detection (Image processing)
          Feature extraction
          Cultural policy
          Genetic algorithms
      keyword:
        copyrightHolder:EADH: The European Association for Digital Humanities
        copyrightYear:2026
        Grab-Cut segmentation
        improved Canny operator
        inLanguage:en
        intangible cultural heritage paper-cut patterns
        intelligent extraction
        publisher:Oxford University Press
        sameAs:https://dx.doi.org/10.1093/llc/fqaf006
      ab: As a unique intangible cultural heritage in Chinese traditional culture, paper-cut art is now facing the dilemma of inheritance and development, and with the death of paper-cut artists and the damage and loss of paper-cut works, some paper-cut types also disappear. Therefore, the digital protection of paper-cut art is urgent. This research is based on the improved genetic algorithm adaptive optimization of Canny operator threshold and Grab-Cut algorithm to achieve intelligent extraction and segmentation of intangible cultural heritage paper-cut patterns. First, the collected paper-cut images are smoothed by bilateral filtering to improve the image quality. Second, based on the Canny operator optimized by the improved genetic algorithm, the overall contour of the paper-cut pattern is extracted. Then, the Grab-Cut algorithm is designed to segment the contours of decoupage design elements in a targeted way, and the vector image is processed by CDR software to obtain an independent editable vector image. Finally, the contour extraction experiments of different kinds of paper-cut images are compared by different algorithms. The results show that the method proposed in this article can effectively detect the true edge of the pattern in paper-cut images and complete the extraction of the pattern contour, and the accuracy of the segmentation pixels of each design element of paper-cut pattern is greater than 96 per cent. It provides a new method for the digital protection and innovative application of intangible cultural heritage paper-cut art.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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