Measuring the Performance of Shape Similarity Retrieval Methods
Measuring the Performance of Shape Similarity Retrieval Methods
复制标题
测量形状相似性检索方法的性能
DOI：
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复制
发表时间：
2001
影响因子：
4.5
通讯作者：
Mats Carlin
中科院分区：
文献类型：
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作者：
Mats Carlin
当对具有对象的图像或绘图的大型数据库进行数据挖掘时，需要搜索具有形状相似性的对象。根据最近的综述论文，比较不同的形状相似性检索方法和系统的问题在很大程度上被忽视的研究界，由于这种比较的主观性质。事实上，形状相似性检索系统的评价只能参考一个特定的应用程序，在我们的情况下检索铝型材图纸。在本文中，我们提出了五个不同的新的性能指标的形状相似性检索。我们已经应用了六个不同的功能集，包括骨架，矩，傅立叶和模糊/对称功能的方法。结果清楚地表明，形状相似性检索是应用程序和表示依赖，可以通过一些独立的方法进行评估。
When datamining large databases with images or drawings of objects, there is a need to search for objects with a shape similarity. According to recent overview papers the issue of comparing different shape similarity retrieval methods and systems has largely been neglected in the research community due to the subjective character of such comparisons. Indeed, the evaluation of a shape similarity retrieval system can only be made with reference to a particular application, in our case retrieval of drawings of aluminum sections. In this paper we propose five different new performance measures for shape similarity retrieval. We have applied the methods on six different feature sets including skeleton, moment, Fourier, and fuzzy/symmetry features. The results clearly show that shape similarity retrieval is both application and representation dependent and can be evaluated by a number of independent methods.