Near-duplicate image detection with cascade method

Yu Cao
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Abstract

In this paper, a novel scheme to tackle the task of near-duplicate image detection is presented. The scheme is based on a two-level image similarity measure strategy, which reduces the overall computational cost. The second-level similarity measure considering spatial position relationship can find the small similar objects in two images. Given two input images, which are represented with multiple local features, the proposed algorithm can assert whether the reference image is a near-duplicate of the query image or not. The algorithm is demonstrated on some image or video keyframe pairs with scale change, viewpoint change, blur, noise and spatial deformation, which are extracted from INRIA copy dataset, etc. The experimental results show that proposed algorithm is simple and effective.
级联法近重复图像检测
本文提出了一种解决近重复图像检测问题的新方案。该方案基于两级图像相似度度量策略,降低了总体计算成本。考虑空间位置关系的二级相似性度量可以找到两幅图像中相似的小物体。给定两幅输入图像,并由多个局部特征表示,该算法可以判断参考图像是否与查询图像近似重复。在INRIA复制数据集中提取的具有尺度变化、视点变化、模糊、噪声和空间变形等特征的图像或视频关键帧对上进行了验证。实验结果表明,该算法简单有效。
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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