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

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.