[1]陈思燕,方丽英*.基于K-Means和高斯混合模型的云肩色彩提取方法对比[J].服装学报,2021,6(02):131-137.
　CHEN Siyan,FANG Liying*.Comparative Study of Cloud Shoulder Color Extraction Methods Based on K-Means and Gaussian Mixture Model[J].Journal of Clothing Research,2021,6(02):131-137.
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基于K-Means和高斯混合模型的云肩色彩提取方法对比()
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《服装学报》[ISSN:2096-1928/CN:32-1864/TS]

卷:
第6卷
期数:
2021年02期
页码:
131-137
栏目:
服装信息与工程
出版日期:
2021-04-30

文章信息/Info

Title:
Comparative Study of Cloud Shoulder Color Extraction Methods Based on K-Means and Gaussian Mixture Model
作者:
陈思燕1;  方丽英*2
1.浙江理工大学 服装学院,浙江 杭州,310018; 2.浙江理工大学 国际教育学院,浙江 杭州 310018
Author(s):
CHEN Siyan1;  FANG Liying*2
1.School of Fashion Design and Engineering,Zhejiang Sci-Tech University, Hangzhou 310018, China; 2.School of International Education, Zhejiang Sci-Tech University, Hangzhou 310018, China
分类号:
TS 941.1; TP 391.41
文献标志码:
A
摘要:
为获取传统服饰图像的色彩构成情况,选取极具特色的服饰品云肩,对比K-means和高斯混合模型的色彩提取效果。对云肩原始图像的R,B,G通道进行降噪预处理; 将图像BGR色彩空间转换至RGB与HSV空间,采用肘部法确定最佳类簇数目k值; 分别借助两种算法对图像进行分割与主色彩聚类,从执行效率、分割效果和提取精准度3方面进行对比,确定适合云肩图像的色彩提取方法。实验结果表明:相比高斯混合模型,K-means算法对云肩图像色彩的聚类提取效果更优。
Abstract:
In order to obtain the color composition of traditional clothing images, a highly featured clothing item with cloudy shoulder was selected, and the color extraction effect of K-means and Gaussian mixture model were compared. The R, B and G channels of the original image of cloud shoulder were pre-processed for noise reduction. Then the BGR color space of the image was converted to RGB and HSV space, and the elbow method was used to determine the optimal cluster number k value. Then the image was segmented and the main color clustering was performed through the K-means and Gaussian mixture model, the extraction effect was compared from the three aspects of execution efficiency, segmentation effect and extraction accuracy. The experimental results show that compared with the Gaussian mixture model, the K-means algorithm has a better effect on the cluster extraction of the main colors of cloud shoulder images.

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(责任编辑:邢宝妹)

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更新日期/Last Update: 2020-04-30