Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jul 11:2022:8008796.
doi: 10.1155/2022/8008796. eCollection 2022.

Image Layout and Schema Analysis of Chinese Traditional Woodblock Prints Based on Texture and Color Texture Characteristics in the Environment of Few Samples

Xiaohong Yue  1
Affiliations

Image Layout and Schema Analysis of Chinese Traditional Woodblock Prints Based on Texture and Color Texture Characteristics in the Environment of Few Samples

Xiaohong Yue. Comput Intell Neurosci. .

Retraction in

Abstract

Technology is the means by which all arts, including woodblock prints, are realized. The "kinship" with modern science and technology makes the development history of woodcut art that can also be understood as a technology history. The purpose of the texture expression produced in the creation of contemporary woodcut is to explore the rich texture expression forms made by contemporary representative painters using special material materials and tools in artistic creation, form a painting technique of personalized words, add new aesthetic meaning to art, and lay a foundation for the formation of unique style of Contemporary Art and the creation and development of woodcut texture. With the development of the times and the change of the public's aesthetic taste, the traditional pattern of printmaking needs to be properly transformed if it is to adapt to the modern humanistic environment, which also involves the importance of screen layout and pattern analysis of Chinese traditional woodcut. Based on the analysis of texture and color texture features in a few-sample environment, this paper proposes an automatic classification method for vignetting texture pictures by extracting the corresponding vignetting coefficients, and through experiments to verify that the proposed SILCO has good generalization sex. In the algorithm designed in this paper, the experiment shows that the accuracy P has a 64.7% improvement effect, and the recall r has a 67.8% performance improvement. On the whole, the experimental data show that the comprehensive classification accuracy is more than 57.4%.

PubMed Disclaimer

Conflict of interest statement

The author does not have any possible conflicts of interest.

Figures

Figure 1
Figure 1
Comparison of recursion-based methods and combinatorial-based methods.
Figure 2
Figure 2
Color texture feature extraction model.
Figure 3
Figure 3
Wavelet number of two-layer wavelet packet decomposition.
Figure 4
Figure 4
Recall analysis.
Figure 5
Figure 5
Accuracy analysis.
Figure 6
Figure 6
Feasibility analysis.
Figure 7
Figure 7
Analysis of screen layout and schema extraction efficiency.
Figure 8
Figure 8
The correct rate of color texture classification.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Vidyadharan D. S., Thampi S. M. Evaluating color and texture features for forgery localization from illuminant maps. Multimedia Tools and Applications . 2018;77(16):21131–21161.
    1. Feng H. C., Zhao Z. Y., Zhang J. Y., Pan G. -Q. An evaluation method for fusion feature of digital pattern painting based on super-efficiency DEA model. Binggong Xuebao/Acta Armamentarii . 2017;38(11):2214–2219.
    1. Taemin L., Dongwann K., Ja C. K., SooJin P., Kyunghyun Y. Developing application depend on emotion extraction from paintings. Journal of Digital Contents Society . 2017;18(6):1033–1040.
    1. Rohini S., Soma S. A novel texture based skin melanoma detection using color GLCM and CS-lbp feature. International Journal of Computer Application . 2017;171(5):1–5.
    1. Kharsan N. R., Badnerker S. S. A riview paper on content based image retrieval technique using color and texture feature. International Journal of Engineering Trends and Technology . 2017;43(5):274–278.

Publication types

LinkOut - more resources