CoMo:一种用于图像检索的紧凑复合矩描述符

S. A. Vassou, N. Anagnostopoulos, A. Amanatiadis, Klitos Christodoulou, S. Chatzichristofis
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引用次数: 15

摘要

低层次特征在图像检索中起着至关重要的作用。图像矩可以有效地表示图像内容的全局信息,并且在平移、旋转和缩放下保持不变。本文简要地提出了一种基于矩量的复合压缩低级描述符。为了测试所提出的特征,作者采用视觉词袋表示在两个知名的基准图像数据库上进行实验。在所有测试的不同集合中报告的鲁棒性和高度竞争性检索性能,验证了所提出的描述符引入的有希望的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CoMo: A Compact Composite Moment-Based Descriptor for Image Retrieval
Low level features play a vital role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper briefly presents a moment based composite and compact low-level descriptor for image retrieval. In order to test the proposed feature, the authors employ the Bag-of-Visual-Words representation to perform experiments on two well-known benchmarking image databases. The robust and highly competitive retrieval performances, reported in all tested diverse collections, verify the promising potential that the proposed descriptor introduces.
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