Month: March 2022

AAFS 2022 Recap: Understanding Juror Comprehension of Forensic Testimony: Assessing Jurors’ Decision Making and Evidence Evaluation

By Samantha Springer, a research assistant at the Center for Statistics and Applications in Forensic Evidence (CSAFE)

During the 74th annual American Academy of Forensic Sciences (AAFS) scientific conference, Cassidy Koolmees, a graduate student in legal psychology at Florida International University (FIU), and her colleagues presented a new study entitled Understanding Juror Comprehension of Forensic Testimony: Assessing Jurors’ Decision Making and Evidence Evaluation. This study came after assessing the findings in multiple studies conducted by CSAFE co-director Brandon Garrett et al., who found that a jury’s analysis of forensic testimony was not dependent on the strength of the language used during the testimony. Besides a slight decrease in conviction rates when inconclusive language was used, guilty verdicts remained stable across all conditions that used language indicating a match. This result suggests that the language used to express a match in forensic testimony has little impact on a jury, regardless of the strength of the language or credibility the expert claims.

Building on these findings, Koolmees and her colleagues examined whether jurors could distinguish low-quality testimony from high-quality testimony of forensic experts, using the language guidelines released by the Department of Justice (DOJ) in 2018 as an indicator of quality.

Study participants were put into one of six language-related conditions, where the number of violations of the DOJ language guidelines ranged from zero to five. Participants listened to a full mock trial that included the presentation of forensic evidence. Afterward, they were asked their verdict and how they would rate aspects of the testimony, including confidence in the verdict, clarity of forensic testimony, credibility of the forensic expert, and strength, quality, and usefulness of the forensic evidence.

Most of the dependent variables were found to have no statistical significance between conditions; confidence in the verdict, credibility of the expert, as well as the strength, usefulness, and clarity of the testimony were all consistent across groups.

The only statistically significant difference found between conditions was in the judgment of quality. Only when comparing the conditions of zero guideline violations and four and five violations were there any changes in guilty verdicts, signifying jurors may notice a change in the quality of forensic testimony only when the quality is severely low.

Overall, the study found that, similarly to previous studies, mock jurors are not sensitive to the quality of forensic evidence or to the differences in language used by the experts presenting said evidence. Further research by the FIU group currently being finalized includes versions of the study where jurors are made aware of the DOJ language guidelines before they are presented with expert testimony.

The researchers of the study share CSAFE’s desire for continued education for those involved in criminal trials. Suggestions put forth include simplified jury instructions and a video presentation of instructions. These proposed reforms align with the CSAFE goal of increasing education in forensic evidence for jurors, attorneys, judges, and other relevant parties.

CSAFE supports and oversees substantial contributions to training and education for a wide range of forensic science stakeholders. Explore CSAFE’s available learning opportunities and current training and education research projects at https://forensicstats.org/training-and-education/.

Publications referenced by Koolmees in her study:
How Jurors Evaluate Fingerprint Evidence: The Relative Importance of Match Language, Method Information, and Error Acknowledgment
Brandon Garrett and Gregory Mitchell
Mock Jurors’ Evaluation of Firearm Examiner Testimony
Brandon Garrett, Nicholas Scurich and William Crozier

Implementation and Practice Training and Education

AAFS 2022 Recap: An Internal Validation Study of the TopMatch 3D Scanner for Cartridge Cases

A CSAFE lab technician loads a tray of cartridge cases into the TopMatch 3D scanner.

By Samantha Springer, a research assistant at the Center for Statistics and Applications in Forensic Evidence (CSAFE)

At the 74th annual American Academy of Forensic Sciences (AAFS) scientific conference, Kayli Carrillo, a doctoral candidate at Sam Houston State University, presented a study that showed promising results for the future use of virtual microscopy in assisting forensic examiners with analyzing ballistic evidence. The study, performed by Carrillo and her colleagues at the Harris County Institute of Forensic Sciences in Houston, Texas, utilized a TopMatch VCM system identical to the microscopes used in CSAFE’s ballistics lab. CSAFE’s lab is part of the Roy J. Carver High Resolution Microscopy Facility at Iowa State University.

The internal validation study involved three stages of examination with known and unknown sourced cartridge cases analyzed by multiple examiners. The three phases introduced very few inconclusive determinations, and no matches were determined to be false positives or false negatives. These results indicate a study with a very high internal validity, which shows that the use of virtual comparison microscopy, specifically TopMatch software, can aid in forensic analysis.

Continued research will adopt a fourth step to further evaluate the inconclusive determinations made in the study by examiners. This step will compare such conclusions found when using VCM versus light comparison microscopy, alternatively known as 2D microscopy. Based on the promising findings of this study, the Harris County Institute of Forensic Sciences plans to utilize TopMatch microscopy in the analysis of their cartridge cases.

CSAFE researchers have made great strides in developing statistical and scientific foundations for assessing and matching firearms and toolmarks. Learn more at https://forensicstats.org/firearms-and-toolmark-analysis/.

Firearms and Toolmarks Analysis

Insights: The Effect of Image Descriptors on the Performance of Classifiers of Footwear Outsole Image Pairs

INSIGHT

The Effect of Image Descriptors on the Performance of Classifiers of Footwear Outsole Image Pairs

OVERVIEW

Shoe prints left at a crime scene can often be partially observed, smudgy, or subject to background effects such as dirt or snow, which can make comparing prints to a reference image challenging. Similarly, prints from the same shoe can vary depending on the wearer’s gait, weight and activity during the time of impression. Reliable, qualitative methods have yet to be developed for visually assessing the similarity between impressions. To help develop such methods, researchers funded by CSAFE created an algorithm that extracts image descriptors (well-defined groups of pixels), then tested the algorithm by comparing simulated crime scene images to a study database.

Lead Researchers

Soyoung Park
Alicia Carriquiry

Journal

Forensic Science International

Publication Date

February 2022

Publication Number

IN 128 FW

The Goals

1

Develop a quantitative method for comparing shoe print images.

2

Test this method’s performance against an existing “standard” method to quantify similarity between two images.

The Study

Park and Carriquiry created a study database of impression images, using 48 pairs of shoes which had been worn by volunteers for six months. They then scanned the shoe prints, placing 0 to 10 sheets of paper between the shoes and the scanner to simulate levels of degradation. In all, the researchers obtained 864 reference images, and made 1,728 pairs of images to compare
half of which were mated (coming from the same shoe), and half non-mated.

Meanwhile, the researchers developed an algorithm to compare these pairs using image descriptors, which identify distinct groups of pixels in an image such as corners, lines and blobs. In particular, they used the SURF and KAZE descriptors to identify blobs, and the ORB descriptor to identify corners.

A mated pair of images, scanned at level 0 and level 10 degradation

Using six different combinations of descriptors, the researchers ran their comparisons to determine which model had the best balance of accuracy and computation efficiency, which is required in real-world situations. For a control, they used a proposed method called Phase-Only
Correlation (POC) to compare to the descriptor-based methods.

SURF (Speeded-Up Robust Feature): a descriptor which uses a box filter on integral images

KAZE: meaning “wind” in Japanese, the name refers to the descriptor’s use of nonlinear diffusion filtering

ORB (Oriented FAST and Rotated BRIEF): a combination of two extraction methods, FAST (Features from Accelerated Segment Test) and BRIEF (Binary Robust Independent Elementary Features)

Results

Degradation Level 10

1

All tested models showed promise, with good quality images reaching accuracy of 95% or better, and even blurry images achieving accuracy of 85% to 88%.

2

The models that relied on the SURF and KAZE descriptors outperformed those that relied on ORB.

3

In comparison, the POC model failed to differentiate between mated and non-mated pairs.

Focus on the future

There is a lack of large databases with realistic footwear impressions. A larger database, with different brands and models of shoes, may help develop more robust algorithms for wider use.

Algorithms will likely never replace well-trained examiners, but the more accurate and efficient these algorithms become, the more useful they can be to examiners in their work.