面向自然图像的自适应主色提取方法研究  

Research on Adaptive Main Colors Extraction Algorithm for Natural Images

作　　者：杨慧炯 YANG Hui-jiong(Department of Computer Engineering,Taiyuan Institute of Teehnology,Taiyuan 030008,China)

机构地区：[1]太原工业学院计算机工程系,山西太原030008

出　　处：《微电子学与计算机》2018年第9期99-102,107,共5页Microelectronics & Computer

基　　金：山西省科技攻关项目(20140313025-2);山西省高等学校科技开发项目(20121119)

摘　　要：提出了一种面向自然图像的自适应主色提取算法.对于一幅用户给定的自然图像,算法首先为了避免RGB空间处理时易造成颜色失真的缺陷,将图像的颜色空间转换到Lab空间;然后对图像进行尺寸压缩、图像增强和去噪等预处理以消除图像中的干扰信息且较好地保留细节信息;最后通过将Silhouette轮廓系数与传统K均值聚类算法有机地结合在一起,自适应地提取出自然图像中的最优主色集.对大量拍摄于各种自然环境下的图像进行测试,实验结果表明算法可有效地将自然图像中的主色自动提取出来,且较准确地代表了原图像中的颜色特征.A framework of adaptive main color extraction algorithm for natural image is proposed in order to make the artistic effects of oil painting on computer much more similar to the hand-printed style in color.As for a natural image provided by a user,the algorithm first transforms the color space of the image into the Lab space to avoid the color distortion caused by the RGB spaceprocessing.Then,the natural image is preprocessed through size compression,image enhancement and denoising in order to eliminate the interference information and preserve the detail information to a better extent in the image.Finally,the silhouette contour factoris effectively combined with the traditional K-means clustering algorithm to extract optimal main colors set in the natural image.A quantity of experiments have been conducted on the natural imagesobtained from a variety of natural environments to test the effects.The results show that the algorithm can effectively extract the main colors in a natural image and the maincolors display the representative color features in the original image in a better way.

关 键 词：自然图像 主色提取 自适应 K均值聚类 Silhouette轮廓系数 

分 类 号：TM63[电气工程—电力系统及自动化] TP249[自动化与计算机技术—检测技术与自动化装置]