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Near-duplicate image detection with cascade method

机译:级联法进行近重复图像检测

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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.
机译:本文提出了一种解决近重复图像检测任务的新方案。该方案基于两级图像相似性度量策略,从而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在两个图像中找到小的相似对象。给定两个输入图像,它们用多个局部特征表示,所提出的算法可以断言参考图像是否与查询图像近似重复。从INRIA复制数据集等中提取的具有比例变化,视点变化,模糊,噪声和空间变形的图像或视频关键帧对上演示了该算法。实验结果表明,该算法简单有效。

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