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Content representation and pairwise feature matching method for virtual reconstruction of shredded documents

机译:粉碎文档虚拟重建的内容表示和成对特征匹配方法

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In forensics, virtual reconstruction of shredded documents is a well-known problem. Semi-automatic document reconstruction systems are usually used for virtual reconstruction. Here a content feature extraction, a content feature representation and a 1:1-matching-method for the use in such reconstruction systems are presented. The content representation is given in the form of so-called abstract structure objects (ASO), which are calculated based on foreground information distributions and on color categories. The presented 1:1-matching-method calculates local optima and places these optima in a global context in relation to cut-edge-pair. Experiments were performed on different real-world-datasets with different foreground characteristics. We show the good discrimination power of the presented method for the use in reconstruction systems regardless of the type of foreground information.
机译:在法医学中,碎片文件的虚拟重建是一个众所周知的问题。半自动文件重建系统通常用于虚拟重建。这里,呈现了内容特征提取,内容特征表示和用于这种重建系统的1:1匹配方法。内容表示以所谓的抽象结构对象(ASO)的形式给出,其基于前景信息分布和彩色类别来计算。呈现的1:1匹配方法计算本地Optima,并将这些Optima与剪切侧对的全局上下文置于。在具有不同前景特征的不同现实数据集上进行实验。我们展示了在重建系统中使用的良好辨别力,无论前景信息的类型如何。

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