Computer vision techniques for semi-automatic reconstruction of ripped-up documents
Patrick DE SMET, Johan De Bock, Els Corluy · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
This paper investigates the use of computer vision techniques to aid in the semi-automatic reconstruction of torn or ripped-up documents. First, we discuss a procedure for obtaining a digital database of a given set of paper fragments using a flatbed image scanner, a brightly coloured scanner background, and a region growing algorithm. The contour of each segmented piece of paper is then traced around using a chain code algorithm and the contours are annotated by calculating a set of feature vectors. Next, the contours of the fragments are matched against each other using the annotated feature information and a string matching algorithm. Finally, the matching results are used to reposition the paper fragments so that a jigsaw puzzle reconstruction of the document can be obtained. For each of the three major components, i.e., segmentation, matching, and global document reconstruction, we briefly discuss a set of prototype GUI tools for guiding and presenting the obtained results. We discuss the performance and the reconstruction results that can be obtained, and show that the proposed framework can offer an interesting set of tools to forensic investigators.