Visual Image Retrieval
Visual Image Retrieval
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DOI：
10.1109/34.574790
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发表时间：
1997-02
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有效的图像检索从数据库中的内容，需要使用视觉图像属性，而不是文本标签，以正确的索引和恢复图片数据。检索形状相似性，给定的用户草图模板是特别具有挑战性的，由于难以获得的相似性度量，密切符合人类的共同感知的相似性。在本文中，我们提出了一种技术，这是基于弹性匹配的草图模板在图像中的形状来评估相似性排名。所实现的匹配程度和草图为实现这种匹配所花费的弹性变形能量被用于导出草图与数据库中的图像之间的相似性的度量，并对要显示的图像进行排序。弹性匹配与安排相结合，以提供尺度不变性，并考虑到多对象查询中对象之间的空间关系。从一个原型系统的例子阐述了考虑的有效性的方法和比较性能分析。
Effective image retrieval by content from database requires that visual image properties are used instead of textual labels to properly index and recover pictorial data. Retrieval by shape similarity, given a user-sketched template is particularly challenging, owing to the difficulty to derive a similarity measure that closely conforms to the common perception of similarity by humans. In this paper, we present a technique which is based on elastic matching of sketched templates over the shapes in the images to evaluate similarity ranks. The degree of matching achieved and the elastic deformation energy spent by the sketch to achieve such a match are used to derive a measure of similarity between the sketch and the images in the database and to rank images to be displayed. The elastic matching is integrated with arrangements to provide scale invariance and take into account spatial relationships between objects in multi-object queries. Examples from a prototype system are expounded with considerations about the effectiveness of the approach and comparative performance analysis.