<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper first explores the composition of visual elements in modern digital media artworks, extracts the graphical element features of visual elements by improved SIFT algorithm, and classifies and recognizes the graphical elements using by SVM algorithm. Secondly, the extracted and categorized graphical elements are represented by Laplace feature vector correlation spectra in combination with spectral graph theory to study the mutual relationships between the graphical elements. Finally, some graphic elements in modern digital media artworks are used as examples to explore the performance and interrelationship of graphic feature extraction, recognition, and classification. The results show that the vector eigenvalues of spectral graph theory are categorized into [0], (0,100], (100,200], [200, ∞), and the corresponding interrelationships are one-to-one, one-to-many, many-to-one, many-to-many, respectively.</p>
</abstract>

This paper first explores the composition of visual elements in modern digital media artworks, extracts the graphical element features of visual elements by improved SIFT algorithm, and classifies and recognizes the graphical elements using by SVM algorithm. Secondly, the extracted and categorized graphical elements are represented by Laplace feature vector correlation spectra in combination with spectral graph theory to study the mutual relationships between the graphical elements. Finally, some graphic elements in modern digital media artworks are used as examples to explore the performance and interrelationship of graphic feature extraction, recognition, and classification. The results show that the vector eigenvalues of spectral graph theory are categorized into [0], (0,100], (100,200], [200, ∞), and the corresponding interrelationships are one-to-one, one-to-many, many-to-one, many-to-many, respectively.

Interrelationship of Visual Elements of Digital Media Artworks Based on Spectral Graph Theory

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper first explores the composition of visual elements in modern digital media artworks, extracts the graphical element features of visual elements by...

Interrelationship of Visual Elements of Digital Media Artworks Based on Spectral Graph Theory

Online veröffentlicht: 08. Nov. 2023

Seitenbereich: -

Eingereicht: 22. Dez. 2022

Akzeptiert: 19. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01031

Schlüsselwörter
SIFT algorithm, SVM algorithm, Spectral graph theory, Visual elements, Digital media art, Laplace representation

© 2023 Jian Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Interrelationship of Visual Elements of Digital Media Artworks Based on Spectral Graph Theory

Online veröffentlicht: 08. Nov. 2023

Seitenbereich: -

Eingereicht: 22. Dez. 2022

Akzeptiert: 19. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01031

SchlüsselwörterSIFT algorithm, SVM algorithm, Spectral graph theory, Visual elements, Digital media art, Laplace representation

© 2023 Jian Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
SIFT algorithm, SVM algorithm, Spectral graph theory, Visual elements, Digital media art, Laplace representation