One of important components in an image retrieval system is selecting a distance measure to compute rank between two objects. In this paper, several distance measures were researched to implement a foliage plant retrieval system. Sixty kinds of foliage plants with various leaf color and shape were used to test the performance of 7 different kinds of distance measures: city block distance, Euclidean distance, Canberra distance, Bray-Curtis distance, x2 statistics, Jensen Shannon divergence and Kullback Leibler divergence. The results show that city block and Euclidean distance measures gave the best performance among the others.
翻译：图像检索系统中的一个重要组成部分是选择一个测距尺度来计算两个对象之间的排位。在本文中,对几个测距尺度进行了研究,以实施树叶植物检索系统。使用60种具有不同叶色和形状的树叶植物来测试7种不同距离测量的性能:城市街区距离、欧几里德距离、堪培拉距离、Bray-Curtis距离、x2统计数据、Jensen Shannon差异和Kullback Leiberr差异。结果显示,城市街区和欧几里德距离测量的性能优异。
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