Color Feature Based Dominant Color Extraction
Color Feature Based Dominant Color Extraction
复制标题
基于颜色特征的主色提取
DOI：
10.1109/access.2022.3202632
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发表时间：
2022
期刊：
影响因子：
3.9
通讯作者：
Mukai Nobuhiko
中科院分区：
文献类型：
--
作者：
Chang Youngha;Mukai Nobuhiko
图像中的主色可用于图像搜索、颜色编辑、调色板生成和若干其他应用。传统上，使用基于聚类或直方图的方法来提取主色。然而，这些方法不能提取小区域的主色，这是必不可少的配色方案的分析。这项研究开发了一种方法来自动提取主色的基础上，通常被认为是由人类观察者分析配色方案时的颜色特征。该方法首先在CIELAB颜色空间中利用K-means算法和分割图像的区域邻接图（RAG）的图割计算初始主色候选。然后，算法计算每个聚类的饱和度、对比度和面积等颜色特征，并在此基础上提取主色。我们的方法可以提取突出的颜色从小的图像区域作为主色，这是不可能使用传统的方法。
The dominant colors in an image can be used for image search, color editing, palette generation, and several other applications. Conventionally, dominant colors are extracted using clustering or histogram-based methods. However, these methods cannot extract the dominant colors of small regions, which are essential for the analysis of color schemes. This study developed an approach to automatically extract dominant colors based on color features that are typically considered by human observers when analyzing color schemes. The proposed method first calculates the initial dominant color candidates using the K-means algorithm in the CIELAB color space and the graph cut of a region adjacency graph (RAG) of the segmented image. Next, the algorithm calculates the color features such as the saturation, contrast, and area of each cluster, based on which it extracts the dominant colors. Our method can extract prominent colors from small image regions as the dominant colors, which is not possible using conventional methods.