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线性的地球移动距离准确近似方法

Accurate Approximation of the Earth Mover’s Distance in Linear Time

  • 摘要: 颜色描述符是基于内容的图像检索中使用的一种重要特征。主颜色描述符DCD通过颜色量化,描述了图像中一些感知上主导的颜色。基于DCD的图像检索,提出使用earth mover's 距离EMD和最优的颜色组合距离来度量两幅图像的不相似性。尽管能得到好的检索结果,两种方法都太费时,以至于能用于大的图像数据库。为解决这个问题,我们提出了一种新的距离函数,以线性地计算近似的地球移动距离。为在线性条件下计算不相似性,所提出的方法运用多维颜色空间的空间填充曲线。为提高准确性,所提出方法使用了多曲线并调整颜色的位置。这样,我们的方法获得了数量级的时间改进,同时错误小。我们进行了广泛的实验,以说明所提出方法有效且高效。这些结果显示我们的方法线性地获得了几乎与EMD相似的结果。

     

    Abstract: Color descriptors are one of the important features used in content-based image retrieval. The dominant color descriptor (DCD) represents a few perceptually dominant colors in an image through color quantization. For image retrieval based on DCD, the earth mover's distance (EMD) and the optimal color composition distance were proposed to measure the dissimilarity between two images. Although providing good retrieval results, both methods are too time-consuming to be used in a large image database. To solve the problem, we propose a new distance function that calculates an approximate earth mover's distance in linear time. To calculate the dissimilarity in linear time, the proposed approach employs the space-filling curve for multidimensional color space. To improve the accuracy, the proposed approach uses multiple curves and adjusts the color positions. As a result, our approach achieves order-of-magnitude time improvement but incurs small errors. We have performed extensive experiments to show the effectiveness and efficiency of the proposed approach. The results reveal that our approach achieves almost the same results with the EMD in linear time.

     

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