Determining region color by using maximum colorfulness
Determining region color by using maximum colorfulness
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DOI：
10.1109/cgip58526.2023.00010
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
Youngha Chang;S. Saito
中科院分区：
文献类型：
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作者：
Youngha Chang;S. Saito
颜色命名被广泛地用作对象属性或图像区域特征。然而，即使对于单色对象，估计适当的颜色名称也很困难，因为像素的明度和色彩通常取决于高光和阴影。本研究提出一种简单且稳健的区域颜色名称估计方法。该算法利用图像区域的颜色分布。具体来说，该方法首先在CIECAM16色彩空间中估计区域的主色调。接下来，检查具有初级色调的像素的色彩分布。用来确定代表性的色彩和明度。最后，在CIECAM16颜色空间中进行分类颜色命名。与该区域的平均颜色相比，该方法可以产生更饱和的颜色。该方法可应用于图像检索、图像索引、对象属性识别、非真实感渲染、颜色变换等多种应用。
Color naming has been widely used as an object attribute or an image region feature. However, estimating appropriate color names is difficult even for single-color objects because the lightness and colorfulness of pixels typically vary depending on the highlight and shade. This study proposes a simple and robust method to estimate the color name of a given region. The proposed algorithm uses the color distribution of the image region. Specifically, this method first estimates the primary hue of the region in the CIECAM16 color space. Next, the colorfulness distribution of pixels with the primary hue is examined. It is used to determine the representative colorfulness and lightness. Finally, categorical color naming is performed in the CIECAM16 color space. Compared with the mean color of the region, the proposed method can produce more saturated colors. This method can be applied to various applications such as image retrieval, image indexing, object attribute recognition, non-photorealistic rendering, and color transformation.