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Proceedings Paper

Optical-coherence-tomography-based algorithm for handwriting forensic analysis
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Paper Abstract

This work describes a new method for handwriting forensic analysis using optical coherence tomography (OCT) images. The region of interest (ROI) in documents signature to be analyzed were pre-selected with a traditional optical analyzer (Docucenter 2000 – Projectina®) equipped with different wavelengths light sources and bandpass filters coupled detector. The ROI where then submitted to OCT to 3D imaging (OCP930SR, Thorlabs Inc.) with optical resolution of 6.0 microns. One original and 5 falsified signatures were produced by 5 different individuals, using a block of 5 sheets of white sulfite paper A4 size and weight of 75 g/m^2, using the same blue ballpoint pen and in the same surface. For pressure pen calibration, were developed a system computer controlled to maintain the pressure constant during writing linear traces, 15 different pressure configuration were applied to each linear trace, resulting in a relation between deformation and applied pressure. An autonomous algorithm was developed to make surface detection, across OCT tomographic images, correct the paper surface curvature, detect and measure deformation on paper due to pen pressure, generating a new image in false color from differential pressure, based in previous calibration. This new image can be considered as a “fingerprint pressure” signature. This methodology may assist the forensic expert in correctly determining the authorship of a signature.

Paper Details

Date Published: 24 February 2020
PDF: 8 pages
Proc. SPIE 11299, AI and Optical Data Sciences, 112990P (24 February 2020); doi: 10.1117/12.2543356
Show Author Affiliations
Anderson Z. de Freitas, Cidade Univ. (Brazil)
Lucas Antonio de Sousa Ribeiro, Cidade Univ. (Brazil)
Osvaldo Negrini Neto, Cidade Univ. (Brazil)
Jorge E. S. Sarkis, Cidade Univ. (Brazil)
Andressa Nascimento Siqueira, Cidade Univ. (Brazil)


Published in SPIE Proceedings Vol. 11299:
AI and Optical Data Sciences
Bahram Jalali; Ken-ichi Kitayama, Editor(s)

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