| Sumario: | 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.
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