Publicado en 3C Empresa – Volume 13, Issue 1 (Ed. 53)

Autores

• Hua He*

Resumen

Abstract

In order to meet the diversified visual aesthetic needs of the public, this paper constructs a digital visual model based on art history theory. Firstly, the SIFT algorithm is used to extract the art scene feature points, and the convolution operation is carried out by Gaussian function to form a three-dimensional scale space. Then the system reconstruction technology is applied to realize the reconstruction of digital images, and the completeness of the reconstructed images is ensured by setting visual symbols. Finally, texture segmentation is performed by combining pixel difference features, and according to the dynamic distribution of the corner points of the art scene, the local binary fitting method is used for the information enhancement and restoration processing of the art image. The results show that the drawing time of the model in this paper is always kept within 4s, and the completeness of the images all reach more than 99%, and the highest clarity can reach 0.99. It is verified that under the guidance of the art history theory, the attributes of the digitized visual culture have been innovated, and the art space has been expanded.

Artículo

Palabras clave

Keywords

Art history theory; digital vision; SIFT algorithm; Gaussian function; system reconstruction technology

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