In order to extract the image path of traditional cultural and creative items, we set the binary image target of such products to be black and the backdrop to be white in this research. We followed the use of image vectorization processing technology. In order to address the issue of edge jaggedness in the traditional cultural and creative product image path extraction process, polygonal contour fitting is utilized to optimize the image paths of these products, resulting in the creation of a vector map of these products. The PCA point cloud alignment technique is used, based on the vector map of traditional cultural and creative products, to identify the attributes of these items and build a model of their traditional cultural and creative product design that incorporates digital art. After choosing dependent and independent variables, traditional cultural and creative product design, including digital art aspects, is studied and analyzed using linear quantile regression. The findings demonstrate that all of the value-added ratio’s coefficients are significant and bigger at the 0.2 and 0.95 quantile points, suggesting that raising the ratio can aid in the merger of digital art and more established creative and cultural sectors. The medium (M=3.586) and small standard deviation of the traditional cultural and creative items incorporating digital art suggest that the use function and cost-effectiveness of these products have a stronger influence on purchase motivation. This research encourages the fusion of digital art components with conventional cultural and artistic output in order to give traditional culture a fresh lease of life in the information era.