| 一种基于聚类的彩色图像分色算法 | |
| 郏宣耀 ; 滕少华 ; JIA Xuan-yao ; TEN Shao-hua | |
| 2010-06-09 ; 2010-06-09 | |
| 关键词 | 单遍聚类 K-均值聚类 分色 调色板 Once-clustering K-means clustering color separation color palette TP391.41 |
| 其他题名 | A Clustering-based Color Separation Algorithm |
| 中文摘要 | 图像分色在纺织和印刷等行业中有着广泛而重要的应用,其目的是用尽量少的颜色来描述一幅彩色图像,使得到的分色图像与原图像尽可能的接近。提出一种基于单遍聚类和K-均值聚类相结合的自适应图像分色算法。该算法首先对原图像颜色进行统计学习,由单遍聚类产生初始调色板,然后根据该调色板对原图像的像素点进行K-均值聚类,产生分色图像。实验结果表明,与单纯K-均值聚类算法相比,该算法能在提高分色图像质量的同时进一步减少颜色数。; Color image separation is widely and importantly applied in textile and printing industry,its aim is to use as less kinds of color as possible to describe a piece of true color image and make it much similar to original image.An adaptive color separation algorithm combined of Once-clustering and K-means clustering is presented.This method firstly does the statistic learning of the original image,create the initial color palette by Once-clustering,than clusters the pixels in the original image by K-means according to color palette,then obtains the separated image.The result of the experiment shows that,comparing with simple K-means clustering algorithm,this method could further minish the amount of color at the time of improving the color separation image quality.; 宁波大红鹰职业技术学院软件学院基金资助(I0603) |
| 语种 | 中文 ; 中文 |
| 内容类型 | 期刊论文 |
| 源URL | [http://hdl.handle.net/123456789/55212]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | 郏宣耀,滕少华,JIA Xuan-yao,等. 一种基于聚类的彩色图像分色算法[J],2010, 2010. |
| APA | 郏宣耀,滕少华,JIA Xuan-yao,&TEN Shao-hua.(2010).一种基于聚类的彩色图像分色算法.. |
| MLA | 郏宣耀,et al."一种基于聚类的彩色图像分色算法".(2010). |
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