A Discussion on Automatic Reassembling of Shredded Paper via Similarity Measurement Models

DOI

10.2991/ccit-14.2014.42How to use a DOI?

Keywords

resembling of shredded paper, image processing, similarity measurement, characteristic vector

Abstract

Reassembling of shredded paper from a collection of randomly mixed fragments is a common application of computer vision technique. It plays an irreplaceable role in several applied disciplines, such as classical forensics, archaeology, and military intelligence. In this paper we address the reassembly problem using a similarity measurement model applied in data mining. We propose a general process model for automatically analyzing the similarity between the gray value matrices of the scanned images in order to judge if they were adjacent to each other in the original document. Here we take both the Euclid distance and the characteristic values into consideration when it comes to similarity measurement. The implementation results provided demonstrate the validity of the proposed technique.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fanyu Meng
AU  - Wen Qian
PY  - 2014/01
DA  - 2014/01
TI  - A Discussion on Automatic Reassembling of Shredded Paper via Similarity Measurement Models
BT  - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
PB  - Atlantis Press
SP  - 160
EP  - 162
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.42
DO  - 10.2991/ccit-14.2014.42
ID  - Meng2014/01
ER  -