Abstract
Hand shredded content-less pages reassembly is a challenging task. This has applications in forensics and fun games. The process is even more tedious when the number of pages from which the fragments are obtained is unknown. An iterative framework to solve the jigsaw puzzles of multiple hand shredded content-less pages has been proposed in this paper. This framework makes use of the shape-based information alone to solve the puzzle. All pairs of fragments are matched using the normalized shape-based features. Then, incorrect matches between the fragments are pruned using three scores that measure the goodness of the alignment. Finally, a graph-based technique is used to densely arrange the fragments for the global reassembly of the page(s). Experimental evaluation of our proposed framework on an annotated dataset of shredded documents shows the efficiency in the reconstruction of multiple content-less pages from arbitrarily torn fragments and performance metrics have been proposed to numerically evaluate the reassembly.
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Lalitha, K.S., Das, S., Menon, A., Varghese, K. (2017). Simultaneous Reconstruction of Multiple Hand Shredded Content-Less Pages Using Graph-Based Global Reassembly. In: Mukherjee, S., et al. Computer Vision, Graphics, and Image Processing. ICVGIP 2016. Lecture Notes in Computer Science(), vol 10481. Springer, Cham. https://doi.org/10.1007/978-3-319-68124-5_7
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