Institute of Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands.
Skin Res Technol. 2010 Feb;16(1):109-13. doi: 10.1111/j.1600-0846.2009.00405.x.
BACKGROUND/PURPOSE: We compare the effectiveness of 10 different color representations in a content-based image retrieval task for dermatology.
As features, we use the average colors of healthy and lesion skin in an image. The extracted features are used to retrieve similar images from a database using a k-nearest-neighbor search and Euclidean distance. The images in the database are divided into four different color categories. We measure the effectiveness of retrieval by the average percentage of retrieved images that belong to the same category as a query image.
We found that the difference of the colors of lesion and healthy skin is a better color descriptor than the pair of these colors. We obtained the best results with the CIE-Lab color representation [75+/-3.8% (95% confidence interval) correct retrieval rate for k=11], followed by CIE-Luv and CIE-Lch.
CIE-Lab is the most effective color space for content-based image retrieval of dermatological images. The difference of the colors of lesion and healthy skin in an image is a better color descriptor than the pair of these colors.
背景/目的：我们比较了在皮肤科基于内容的图像检索任务中，10 种不同颜色表示的有效性。
作为特征，我们使用图像中健康和病变皮肤的平均颜色。使用提取的特征，通过 k-最近邻搜索和欧几里得距离，从数据库中检索相似的图像。数据库中的图像被分为四个不同的颜色类别。我们通过检索到的图像中属于查询图像同一类别的平均百分比来衡量检索的有效性。
我们发现病变和健康皮肤颜色的差异比这两种颜色的组合更适合作为颜色描述符。我们使用 CIE-Lab 颜色表示（k=11 时的正确检索率为 75+/-3.8%（95%置信区间））获得了最佳结果，其次是 CIE-Luv 和 CIE-Lch。
CIE-Lab 是皮肤科图像基于内容的图像检索最有效的颜色空间。图像中病变和健康皮肤颜色的差异比这两种颜色的组合更适合作为颜色描述符。
