|16-November-2022||16:00 (4:00 pm) PST|
|16-November-2022||19:00 (7:00 pm) EST|
|17-November-2022||00:00 (00:00 ) GMT|
|17-November-2022||02:00 (02:00 am) SAST|
|17-November-2022||12:00 (12:00 pm) NZST|
Speaker – Mike Wakshull
Topic – Quantitative Techniques for Writer Identification
Identification of handwriting relies on the document examiner’s ability to discover the variability of the subject’s known writing. Although qualitative assessment is prone to judgment error by the document examiner, variability in forensic document examination is often presented in qualitative rather than quantitative terms. Qualitative analysis is typically neither repeatable nor reproducible. A quantitative approach to writer identification can and should be used to reduce bias and errors in document examiners’ opinions.
Literature shows that variability of the proportions of height and width of a person’s written letters and words remains stable within common cause variability across writing sessions. This presentation applies aspects of statistical process control to determine whether a writer of a known document is a potential author of a questioned document, based on such variability.
For example: The ratio of the height of lower case letters extending into the upper zone and height of lower case letters remaining in the middle zone is calculated. The ratios of the length of lower case descenders to the height of middle zone letters are calculated. For each calculated ratio a run chart is created for the ratios of the known writing. The same is performed for the slant angle of a given letter. In the book Questioned Documents, author Albert Osborn presented evidence for consistency of the ratio of the height and width of signatures across writing sessions.
The standard deviation of the ratios or angles are computed to one, two, and three sigma. These measurements are plotted to create a control chart.
The measurement of the angle or ratio of the questioned writing is plotted on the control chart to determine how the questioned writing compares to the known writing with respect to the variability of the known writing. The number of standard deviations from the mean of the known writing is explored to determine writer identification.
The null hypothesis is if the ratio of the given letters in the questioned writing falls beyond 2.5 standard deviations from the mean the questioned writing may have been written by a person other than the known writer. The result is an indicator of authorship rather than a conclusive determination.
Mike Wakshull , vice president of SAFE, is a state and federal court-qualified forensic document examiner located in Temecula, CA. He applies his science education and training to partner with legal clients to dissect evidence presented in handwritten and computer-generated questioned documents. He has worked on cases from 28 states and 5 countries.
High quality results are presented to his clients using digital and optical microscopes, video spectral comparator (VSC80), electrostatic detection devices (ESDA), Photoshop, Acrobat Pro, NEGA software, high grade digital scanners, a large research library, and more.
Mike authored three books on the topic of forensic document examination. Mike has presented at international forensics conferences, California Lawyers Association, and California District Attorneys Association, and others.