On stability of signature-based similarity measures for content-based image retrieval
On stability of signature-based similarity measures for content-based image retrieval
复制标题
基于签名的相似性度量在基于内容的图像检索中的稳定性
DOI：
10.1007/s11042-012-1334-3
复制
发表时间：
2014
影响因子：
3.6
通讯作者：
T. Seidl
中科院分区：
文献类型：
--
作者：
C. Beecks;S. Kirchhoff;T. Seidl
对于当今基于内容的检索系统来说，从大型图像数据库中检索相似的图像是一项具有挑战性的任务。为了提高检索性能，这些系统经常通过表达图像模型和自适应相似性度量来捕获用户的相似性概念。在查询端，与存储在数据库端的图像模型相比，图像模型的质量可能存在显著差异。因此，为了保持高检索性能，相似性度量必须对这些单独的质量变化具有鲁棒性。在本文中，我们研究了基于签名的相似性度量家族在基于内容的图像检索中的鲁棒性。为此，我们引入了平均精度稳定性的一般概念，它衡量了相似性度量在查询和数据库端之间质量变化方面的稳定性。除了平均精度稳定性的数学定义之外，我们还包括主要基于签名的相似性度量的性能评估，重点关注它们在通过不同质量的示例查询图像数据库方面的稳定性。我们对最近的基准图像数据库的性能评估表明，最高的检索性能并不一定与最高的稳定性相一致。
Retrieving similar images from large image databases is a challenging task for today’s content-based retrieval systems. Aiming at high retrieval performance, these systems frequently capture the user’s notion of similarity through expressive image models and adaptive similarity measures. On the query side, image models can significantly differ in quality compared to those stored on the database side. Thus, similarity measures have to be robust against these individual quality changes in order to maintain high retrieval performance. In this paper, we investigate the robustness of the family of signature-based similarity measures in the context of content-based image retrieval. To this end, we introduce the generic concept ofaverage precision stability, which measures the stability of a similarity measure with respect to changes in quality between the query and database side. In addition to the mathematical definition of average precision stability, we include a performance evaluation of the major signature-based similarity measures focusing on their stability with respect to querying image databases by examples of varying quality. Our performance evaluation on recent benchmark image databases reveals that the highest retrieval performance does not necessarily coincide with the highest stability.
影响因子：
2.4
作者：
Bo-Gun Park;Kyoung Mu Lee;Sang Uk Lee
通讯作者：
Bo-Gun Park;Kyoung Mu Lee;Sang Uk Lee
影响因子：
19.5
作者：
Rubner, Y;Tomasi, C;Guibas, LJ
通讯作者：
Guibas, LJ
自适应分箱颜色直方图的分析与应用
影响因子：
4.5
作者：
W. Leow;Rui Li
通讯作者：
Rui Li