Automatic ink mismatch detection for forensic document analysis. Issue 11 (November 2015)

• Record Type: Journal Article
• Authors: Khan, Zohaib; Shafait, Faisal; Mian, Ajmal
• Is Part Of: Pattern recognition. Volume 48:Issue 11(2015:Nov.)
• Page Start: 3615
• Page End: 3626
• Publication Date: 2015-11
• Subjects: Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2015.04.008
• Languages: English
• ISSNs: 0031-3203

Abstract

<abstract abstract-type="author" id="ab0005"> <title id="sect0005">Abstract</title> <sec> <p id="sp0075">A key aspect of handwritten document examination is to investigate whether some portion of the text was modified, altered or forged with a different pen. This paper demonstrates the use of hyperspectral imaging for ink mismatch detection in a handwritten note. We propose a novel joint sparse band selection technique that selects informative bands from hyperspectral images for accurate ink mismatch detection. We have developed an end-to-end camera-based hyperspectral document imaging system and collected a database of handwritten notes which has been made publicly available. Algorithmic solutions are presented to handle specific challenges in camera-based hyperspectral document imaging. Extensive experiments show that the proposed band selection method selects the most informative bands and improves average accuracy up to 15%, compared to using all bands.</p> </sec> </abstract>