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    Image Replica Detection based on Support Vector Classifier

    机译:基于支持向量分类器的图像复制检测

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    In this paper, we propose a technique for image replica detection. By replica, we mean equivalent versions of a given reference image, e.g. after it has undergone operations such as compression, filtering or resizing. Applications of this technique include discovery of copyright infringement or detection of illicit content. The technique is based on the extraction of multiple features from an image, namely texture, color, and spatial distribution of colors. Similar features are then grouped into groups and the similarity between two images is given by several partial distances. The decision function to decide whether a test image is a replica of a given reference image is finally derived using Support Vector Classifier (SVC). In this paper, we show that this technique achieves good results on a large database of images. For instance, for a false negative rate of 5 % the system yields a false positive rate of only 6·10~(-5).
    机译:在本文中,我们提出了一种用于图像副本检测的技术。复制品是指给定参考图片的等效版本,例如经过压缩,过滤或调整大小等操作后。该技术的应用包括发现侵犯版权或检测非法内容。该技术基于从图像中提取多个特征,即纹理,颜色和颜色的空间分布。然后将相似特征分组,并通过几个局部距离给出两个图像之间的相似性。最终,使用支持向量分类器(SVC)得出决定测试图像是否是给定参考图像的副本的决定函数。在本文中,我们证明了该技术在大型图像数据库上取得了良好的效果。例如,对于5%的假阴性率,系统仅产生6·10?(-5)的假阳性率。

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