标题： 基于快速压缩的相似性度量及其在基于内容的图像检索中的应用 显示英文标题

标题： A fast compression-based similarity measure with applications to content-based image retrieval

摘要： 基于压缩的相似性度量在多种数据类型的应用中被有效使用，且基本上是一种无参数的方法。然而，这些问题在应用于中等到大型数据集时很少被解决。 本文提出了一种基于字典压缩的相似性度量方法，即快速压缩距离（FCD），该方法降低了这些方法的复杂性，同时性能没有下降。 在此基础上定义了一个基于内容的颜色图像检索系统，可以与基于不变颜色特征的最先进的方法相媲美。 通过FCD，通过对比文献中已分析过的数据集更大的数据集进行实验，可以获得对基于压缩技术的更好理解。 显示英文摘要

摘要： Compression-based similarity measures are effectively employed in applications on diverse data types with a basically parameter-free approach. Nevertheless, there are problems in applying these techniques to medium-to-large datasets which have been seldom addressed. This paper proposes a similarity measure based on compression with dictionaries, the Fast Compression Distance (FCD), which reduces the complexity of these methods, without degradations in performance. On its basis a content-based color image retrieval system is defined, which can be compared to state-of-the-art methods based on invariant color features. Through the FCD a better understanding of compression-based techniques is achieved, by performing experiments on datasets which are larger than the ones analyzed so far in literature.