Digital Analysis for Van Gogh's Painting

Authors

Yuqing Liu, 1. School of Information Science and Engineering, Yunnan University, Kunming 650091, China;;2. Huazhong University of Science and Technology, Wuhan 430074, China;
Yuanyuan Pu, 1. School of Information Science and Engineering, Yunnan University, Kunming 650091, China;;
Yangfu Ren, 1. School of Information Science and Engineering, Yunnan University, Kunming 650091, China;;
Xu Dan, 1. School of Information Science and Engineering, Yunnan University, Kunming 650091, China;;

Abstract

Abstract: Usually, Sparse Coding can be used to extract image characteristics for analyzing the style of visual art works, while researchers always don't do deep data mining on the trained basis function. The basic functions that could reflect the interior characteristics of a stylish image were trained based on Sparse Coding on art works. The spatial and higher-order characteristic statistics were figured out. Van Gogh's art works of different periods were analyzed through normalized mutual information computing using trained basis function's Gabor transform power, in order to find the diversity of style. The simulation results show that data mining on basis function can digitalize the intuitive feeling for basis function, and can distinguish the art styles of different works to a certain extent, and finally can provide reference for the criticism of art works.

Recommended Citation

Liu, Yuqing; Pu, Yuanyuan; Ren, Yangfu; and Dan, Xu (2020) "Digital Analysis for Van Gogh's Painting," Journal of System Simulation: Vol. 27: Iss. 4, Article 15.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss4/15

First Page

779

Revised Date

2014-04-11

DOI Link

https://doi.org/

Last Page

785

CLC

TP391.4

Recommended Citation

Liu Yuqing, Pu Yuanyuan, Ren Yangfu, Xu Dan. Digital Analysis for Van Gogh's Painting[J]. Journal of System Simulation, 2015, 27(4): 779-785.