Printer identification using page geometric distortion on text lines

Abstract

In this paper, we propose novel printer identification algorithms based on page geometric distortion features on text lines. The features include Page Text Line Slope (PTLS) sequence and Page Text Line Interval (PTLI) sequence which are applied to describe the page geometric distortion in horizontal and vertical directions, respectively. The similarity measure of two feature sequences with different length can be presented by the Matching Euclidean Distance. Four printer identification algorithms are proposed to identify the printer source. The proposed algorithms do not need to restore the reference document manually, and maintain high performance even when the document has partial content.