Evaluating color and texture features for forgery localization from illuminant maps

Vidyadharan, Divya S.; Thampi, Sabu M.

doi:10.1007/s11042-017-5574-0

Cited by 4 publications

(1 citation statement)

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“…As a practical “tool” for information dissemination, ancient woodcut prints have gone through a process of social and cultural accumulation [ 1 ]. With the development of society and the needs of aesthetic culture, modern woodcut artists have enriched the representation of the patterns in woodcut prints and brought more space for exploration by integrating the different artistic characteristics of Chinese and Western prints in their creations [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

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

Yue¹

2022

Computational Intelligence and Neuroscience

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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%.

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Section: Introductionmentioning

confidence: 99%