2021
DOI: 10.3390/sym13101822
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Comprehensive Evaluation Method of Ethnic Costume Color Based on K-Means Clustering Method

Abstract: Color is the external manifestation of ethnic minority culture, and the costume of each ethnic group has its objective color matching rules. In the color design of minority costumes, there is often a lack of scientific evaluation methods. Aiming at this problem, this article proposed a comprehensive evaluation method, based on the K-Means clustering method, for evaluating color matching schemes of minority costumes. We used the K-Means clustering method to analyze the objective laws of minority costume colors,… Show more

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Cited by 9 publications
(3 citation statements)
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References 23 publications
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“…Thompson et al [38] proposed a novel color quantization (CQ) method based on the online k-means formula, using adaptive and efficient cluster center initialization and quasi-random sampling to achieve deterministic, rapid, and high-quality quantization [39]. By integrating the Analytic Hierarchy Process (AHP), Zhao et al [40] introduced the GRA-TOPSIS evaluation method to rank and rate ethnic minority costume color schemes, finding KMA beneficial for refining color scheme designs. Based on KMA, Basar et al [41] introduced an innovative adaptive initialization technique in RGB histogram analysis to determine the number of clusters and locate initial cluster centroids, assisting the standard k-means algorithm in tackling color image segmentation challenges.…”
Section: K-means Clustering Methodsmentioning
confidence: 99%
“…Thompson et al [38] proposed a novel color quantization (CQ) method based on the online k-means formula, using adaptive and efficient cluster center initialization and quasi-random sampling to achieve deterministic, rapid, and high-quality quantization [39]. By integrating the Analytic Hierarchy Process (AHP), Zhao et al [40] introduced the GRA-TOPSIS evaluation method to rank and rate ethnic minority costume color schemes, finding KMA beneficial for refining color scheme designs. Based on KMA, Basar et al [41] introduced an innovative adaptive initialization technique in RGB histogram analysis to determine the number of clusters and locate initial cluster centroids, assisting the standard k-means algorithm in tackling color image segmentation challenges.…”
Section: K-means Clustering Methodsmentioning
confidence: 99%
“…It was used to help the company re-plan the color scheme of its wardrobe products. Zhao et al [17] utilized the K-Means clustering method to analyze the objective law of Yi costume colors. Based on the features of Yi costume's primary colors in the HSV color space, they proposed objective evaluation indicators to evaluate the color scheme and help improve it.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In the context of image color extraction, statistical analysis methods such as clustering algorithms (e.g., K-Means and DBSCAN algorithms) are commonly employed. Zhao et al used the K-means clustering method to analyze the color patterns of Yi clothing, and transformed the corresponding color patterns into objective evaluation indicators [14]. Tian et al used a developed Kmeans clustering algorithm to classify the surface color of buildings after extracting them from their background environment [15].…”
Section: Introductionmentioning
confidence: 99%