A rotation and scale invariant descriptor for shape recognition

A. D. Lillo, G. Motta, J. Storer
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引用次数: 2

Abstract

We address the problem of retrieving the silhouettes of objects from a database of shapes with a translation and rotation invariant feature extractor. We retrieve silhouettes by using a “soft” classification based on the Euclidean distance. Experiments show significant gains in retrieval accuracy over the existing literature. This work extends the use of our previously employed feature extractor and shows that the same descriptor can be used for both texture [3] and shape recognition.
用于形状识别的旋转和尺度不变描述符
我们解决了用平移和旋转不变特征提取器从形状数据库中检索物体轮廓的问题。我们通过使用基于欧几里得距离的“软”分类来检索轮廓。实验表明,在检索精度显著提高现有文献。这项工作扩展了我们之前使用的特征提取器的使用,并表明相同的描述符可以用于纹理[3]和形状识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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