Publication

Text-line examination for document forgery detection

Joost van Beusekom, Faisal Shafait, Thomas Breuel

In: International Journal on Document Analysis and Recognition (IJDAR) Online First Pages 1-19 Springer 2012.

Abstract

In this paper, an approach for forgery detection using text-line information is presented. In questioned document examination, text-line rotation and alignment can be important clues for detecting tampered documents. Measuring and detecting such mis-rotations and mis-alignments are a cumbersome task. Therefore, an automated approach for verification of documents based on these two text-line features is proposed in this paper. An in-depth evaluation of the proposed methods shows its usefulness in the context of document security with an area under the ROC curve (AUC) score of AUC = 0.89. The automatic nature of the approach allows the presented methods to be used in high-volume environments.

Weitere Links

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz