Capturing high-resolution digital images for use in forensic document examination.

In the past, pattern disciplines within forensic science have periodically faced criticism due to their subjective and qualitative nature and the perceived absence of research evaluating and supporting the foundations of their practices. Recently, however, forensic scientists and researchers in the field of pattern evidence analysis have developed and published approaches that are more quantitative, objective, and data driven. This effort includes automation, algorithms, and measurement sciences, with the end goal of enabling conclusions to be informed by quantitative models.

Accuracy and reliability of forensic handwriting comparisons.

Forensic handwriting examination involves the comparison of writing samples by forensic document examiners (FDEs) to determine whether or not they were written by the same person. Here we report the results of a large-scale study conducted to assess the accuracy and reliability of handwriting comparison conclusions. Eighty-six practicing FDEs each conducted up to 100 handwriting comparisons, resulting in 7,196 conclusions on 180 distinct comparison sets, using a five-level conclusion scale.

Expansion of the EZSTATSG1 Microsoft Excel Tool for ANSI/ASB Standard 036 Method Validation by the Addition of Weighted Quadratic External Calibration Models Utilizing Five-, Six- or Seven-Point Curves.

The first generation of this Microsoft (MS) Excel (Redmond, WA, USA) tool for method validation, EZSTATSG1, was designed for methods utilizing only linear calibration curves requiring seven calibration levels, and quadratic calibration models were not supported. This significantly improved version, EZSTATSG2, includes all of the features of the original template such as weighted linear calibration models, bias and precision data, dilution integrity and ion suppression. New features in this version include flexible five-, six- or seven-point calibration curves; six weighted quadratic calibration models; standardized residuals by use of frequency plots overlaid with the normal distribution function along with five-number summary data and processed sample stability.

An objective inter-comparison of trash mark constellations generated by manual and automated detection methods.

Trash marks are unintentional markings observed on printed, scanned, or photocopied documents that result from permanent defects or transient material in office machines and can be used for source attribution of questioned documents. Trash mark examinations have been in use in forensic laboratories for decades, yet the method remains relatively untested and relies on training, experience, and anecdotal information to support its validity. This study generated and harnessed objective data to empirically test one of the foundational theories for assessing the origin of photocopied documents: provided trash marks are present in sufficient quantity and/or quality, no two machines will exhibit a constellation of trash marks that is indistinguishable from another.