We are in the era of big data, and art, which has developed along with human history, has been given new vehicles and forms of creation with the use of integrated media technology. This study first introduces artwork and its definition and classification, then briefly describes the definition and development of digital art, and focuses on the development, contribution, and drawbacks of digital artwork NFT (nonfunctional token). This study divided the design model into four layers based on the neural network calculation of factorization machine to build, and the data of each layer was analyzed and processed to build the FNN algorithm model. It was found that the largest proportion of NFT artworks circulating in the trading market is in paintings, at 55%. The HSV color space was selected as the color perception model, and then the picture pixel positions were determined, and redundant pixels were eliminated. To avoid data overflow, the spatial memory occupied by the pixels of the painting was calculated. The results showed that the growth of pixel space complexity was smooth and converged to a straight line, indicating that the original pixel data extracted in this experiment was stable. The circle was selected as the basic guideline for the creation of four digital art paintings with an overall uniform but innovative style.
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