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An Effective Similarity Measurement Algorithm for Dominant Color Feature Matching in Image Retrieval

机译:一种有效的图像检索中主要颜色特征匹配的相似度测量算法

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For the reason that dominant colors can characterize color information of image region and can represent the image using fewer dimensions, dominant color feature is one of the widely used color features in image retrieval. We extract the dominant color feature in HSV color space, and combine it with color distribution information. In this paper, a new similarity measurement algorithm based on block distance is proposed for dominant color matching. Our proposed algorithm not only takes the distance between dominant colors into account, but also the difference of the percentage of dominant colors. The average precision of our algorithm improves about 5% and about 14% respectively compared with block distance and Euclidean distance. Although the average precision of our algorithm is almost equal to quadratic form distance, the computation cost of our algorithm is obviously less than it
机译:由于主色可以表征图像区域的颜色信息并且可以使用较少的维度表示图像,因此主色特征是图像检索中广泛使用的颜色特征之一。我们提取HSV颜色空间中的主要颜色特征,并将其与颜色分布信息相结合。提出了一种基于块距的相似度度量算法进行主色匹配。我们提出的算法不仅考虑了主色之间的距离,而且考虑了主色百分比的差异。与块距和欧几里得距离相比,我们算法的平均精度分别提高了约5%和约14%。尽管我们算法的平均精度几乎等于二次形式距离,但我们的算法的计算成本显然要小于它

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