Automatic Extraction of Color Features from Landscape Images Based on Image Processing

Tan, Cong; Yang, Shaoyu

doi:10.18280/ts.380322

Cited by 6 publications

(4 citation statements)

References 26 publications

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“…The progressive development of contemporary digital technology in software and hardware has assisted landscape research in transforming from qualitative descriptions of color to quantitative instrumental data [4]. Tan (2021) proposed an automatic extraction method for color features from landscape images based on image processing through experiments [24]. Shen, Yao and Li (2021) quantitatively evaluated the color harmony and suitability degree of the plant community and external environment according to the Moon-Spencer (M-S) color harmony theory [2].…”

Section: Color Quantitative Analysis Methodsmentioning

confidence: 99%

“…Human beings obtain 80% of their information through vision, while color is the most sensitive and direct visual information symbol, affecting people's psychological perceptions [23]. Existing studies rarely quantify landscape colors through image analysis [24]. Wang and Hu (2014) analyzed the components of community landscape colors, the specialty of design, factors influencing community landscape color, and the application of color in residential community landscape design [25].…”

Section: Literature Review 21 Color Landscape 211 Definition Of Color...mentioning

confidence: 99%

“…The three constituent colors are main color, auxiliary color, and decorative color, occupying about 70%, 25%, and 5% of the surface area of the product, respectively, which is widely adopted in the color design of color-area ratios [14]. The dominant color features determine landscapes' presentation and visual experience [24]. Urban tones are the overall effect constructed by the three colors and their combined relationships [28], as follows:…”

Section: Elements Of Color Landscapementioning

confidence: 99%

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Chromaticity Analysis on Ethnic Minority Color Landscape Culture in Tibetan Area: A Semantic Differential Approach

Zeng,

Li,

2024

Applied Sciences

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The color–area ratio in ethnic minority areas is one way to perceive cultural elements visually. The openness of spaces, sense of rhythm, and richness of color affect people’s emotions and induce different psychological perceptions. Despite many ethnic minority areas being more colorful than the main traits of Han, there is no systematic quantitative study for the color elements in ethnic minority areas’ landscapes, not to mention the research on the color–area ratio, main and auxiliary colors and embellishments, and layouts. Therefore, this paper studies the color–area ratio of Xiangcheng County in the Tibetan area of Ganzi Prefecture in Sichuan Province. Colors are extracted and quantitatively analyzed from six different aspects using the semantic differential (SD) method and color quantitative analysis method. In this way, low-scored (B group) and high-scored (A group) color landscape samples were extracted from the landscape image library and quantitatively analyzed by ColorImpact V4.1.2. The results show that the ethnic minority group’s color layout is characterized by richer colors and stronger contrasts than the Han group. This paper contributes to academic scholarship regarding color culture in ethnic minority areas. It also provides theoretical support for preserving ethnic minority groups’ cultural heritage and practical insights into color planning for urban and landscape designs.

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Section: Color Quantitative Analysis Methodsmentioning

confidence: 99%

Section: Literature Review 21 Color Landscape 211 Definition Of Color...mentioning

confidence: 99%

Section: Elements Of Color Landscapementioning

confidence: 99%

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Chromaticity Analysis on Ethnic Minority Color Landscape Culture in Tibetan Area: A Semantic Differential Approach

Zeng,

Li,

2024

Applied Sciences

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“…They proved that through the use of convolutional neural network classification on the large dataset, Outex, they were able to obtain results as high as 93.97%. Tan [6] proposed an automatic extraction method of landscape image color features. Firstly, the image was enhanced, and the low-level color features were extracted from the landscape image library.…”

Section: Introductionmentioning

confidence: 99%

Color Regression and Sorting System of Solid Wood Floor

Zhuang

Liu

Yang

et al. 2022

Forests

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Solid wood floors are very common in interior decoration, and their color is an important indicator of product quality, selected in order to achieve the overall aesthetic needed to ensure color consistency. In order to realize the sorting of solid wood floors based on color depth, so that the colors of solid wood floors could be freely graded, one image acquisition system was built to collect 108 solid wood floor images and a set of fast sorting methods for solid wood floor color depth was developed. Among these, 10 solid wood floor images were used as the test set and therefore not sorted, and 98 solid wood floor images were sorted by color depth. Among these, 80 original images were expanded 13 times to 1040, for use as a training set, and 18 were used as a validation set. The color characteristics of solid wood floors in RGB, HSV and Lab color space were extracted, and LightGBM was used to realize the color depth sorting of the solid wood floors. At the same time, two deep learning algorithms, the Vision Transformer as well as Densenet121, improved by means of an adaptive pooling layer, were used to realize the color depth sorting of solid wood floor images of different sizes. The final ranking results showed that the color ranking method using LightGBM to regress the color features exhibited the most harmonious final results.

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Quantitative study on color characteristics of urban park landscapes based on K-means clustering and SD. method

Feng,

Zhang,

et al. 2024

Earth Sci Inform

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Automatic Extraction of Color Features from Landscape Images Based on Image Processing

Cited by 6 publications

References 26 publications

Chromaticity Analysis on Ethnic Minority Color Landscape Culture in Tibetan Area: A Semantic Differential Approach

Chromaticity Analysis on Ethnic Minority Color Landscape Culture in Tibetan Area: A Semantic Differential Approach

Color Regression and Sorting System of Solid Wood Floor

Quantitative study on color characteristics of urban park landscapes based on K-means clustering and SD. method

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