Partial image retrieval using SIFT based on illumination invariant features

Masaki Kobayashi, K. Kameyama
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引用次数: 5

Abstract

In content-based image retrieval (CBIR), the apparent color of objects are strongly influenced by the illumination variation, and this may affect retrieval results adversely. In this work, we propose a framework which can find partial object matchings by using illumination invariant local features, and have achieved image retrieval robust to apparent color changes. Additionally, partial similarities to query images such as logos and trademarks under different illumination conditions were sought, and the system's robustness to apparent color changes were verified.
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基于光照不变性特征的SIFT局部图像检索
在基于内容的图像检索(CBIR)中,物体的表观颜色受到光照变化的强烈影响,这可能会对检索结果产生不利影响。在这项工作中,我们提出了一个框架,该框架可以利用光照不变的局部特征找到部分目标匹配,并实现了图像检索对表观颜色变化的鲁棒性。此外,在不同照明条件下,寻求与查询图像(如徽标和商标)的部分相似度,并验证系统对表观颜色变化的鲁棒性。
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