Author: Molly Doolittle

A database of two-dimensional images of footwear outsole impressions

Footwear outsole images were obtained from 150 pairs of used shoes. The motivation for constructing the database was to enable a statistical analysis of two-dimensional (2D) images of shoe outsoles, to understand within shoe (between replicate images of the same shoe) and between shoe variability, and to develop methods for the evaluation of forensic pattern evidence of shoeprints. Since we scanned the outsole of the used shoes, the images capture not only the outsole pattern design but also the marks that arise from wear and tear and that may help identify the shoe that made the impression. Each shoe in a pair was scanned five times, so that replicate images can be used to estimate within-shoe variability. In total, there are 1500 2D images in the database. The EverOS footwear scanner was used to capture the outsole of each shoe. The scanner detects the weight distribution of the person wearing the shoe when he or she steps on the scanning surface. It images the portions of the outsole that make contact with the scanning surface. The database is a useful resource for forensic scientists or for anybody else with an interest in image comparison. The database we describe, was constructed by researchers in the Center for Statistics and Applications in Forensic Evidence (CSAFE) at Iowa State University.

Statistical Methods for the Forensic Analysis of Geolocated Event Data

A common question in forensic analysis is whether two observed data sets originated from the same source or from different sources. Statistical approaches to addressing this question have been widely adopted within the forensics community, particularly for DNA evidence. Here we investigate the application of statistical approaches to same-source forensic questions for spatial event data, such as determining the likelihood that two sets of observed GPS locations were generated by the same individual. We develop two approaches to quantify the strength of evidence in this setting. The first is a likelihood ratio approach based on modeling the spatial event data directly. The second approach is to instead measure the similarity of the two observed data sets via a score function and then assess the strength of the observed score resulting in the score-based likelihood ratio. A comparative evaluation using geolocated Twitter event data from two large metropolitan areas shows the potential efficacy of such techniques.

Statistical methods for the forensic analysis of geolocated event data

Implementation of a Blind Quality Control Program in a Forensic Laboratory

A blind quality control (QC) program was successfully developed and implemented in the Toxicology, Seized Drugs, Firearms, Latent Prints (Processing and Comparison), Forensic Biology, and Multimedia (Digital and Audio/Video) sections at the Houston Forensic Science Center (HFSC). The program was put into practice based on recommendations set forth in the 2009 National Academy of Sciences report and is conducted in addition to accreditation required annual proficiency tests. The blind QC program allows HFSC to test its entire quality management system and provides a real‐time assessment of the laboratory’s proficiency. To ensure the blind QC cases mimicked real casework, the workflow for each forensic discipline and their evidence submission processes were assessed prior to implementation. Samples are created and submitted by the HFSC Quality Division to whom the expected answer is known. Results from 2015 to 2018 show that of the 973 blind samples submitted, 901 were completed, and only 51 were discovered by analysts as being blind QC cases. Implementation data suggests that this type of program can be employed at other forensic laboratories.

Comparison of three similarity scores for bullet LEA matching

Recent advances in microscopy have made it possible to collect 3D topographic data, enabling more precise virtual comparisons based on the collected 3D data as a supplement to traditional comparison microscopy and 2D photography. Automatic comparison algorithms have been introduced for various scenarios, such as matching cartridge cases[1],[2] or matching bullet striae[3],[4],[5]. One key aspect of validating these automatic comparison algorithms is to evaluate the performance of the algorithm on external tests, that is, using data which were not used to train the algorithm. Here, we present a discussion of the performance of the matching algorithm[6] in three studies conducted using different Ruger weapons. We consider the performance of three scoring measures: random forest score, cross correlation, and consecutive matching striae (CMS) at the land-to-land level and, using Sequential Average Maxima scores, also at the bullet-to bullet level. Cross correlation and random forest scores both result in perfect discrimination of same-source and different-source bullets. At the land-to-land level, discrimination for both cross correlation and random forest scores (based on area under the curve, AUC) is excellent (≥0.90).

Insights: Error Rates, Likelihood Ratios, and Jury Evaluation of Forensic Evidence

INSIGHT

Error Rates, Likelhood Ratios, and Jury Evaluation of Forensic Evidence

OVERVIEW

Forensic examiner testimony regularly plays a role in criminal cases — yet little is known about the weight of testimony on jurors’ judgment.

Researchers set out to learn more: What impact does testimony that is further qualified by error rates and likelihood ratios have on jurors’ conclusions concerning fingerprint comparison evidence and a novel technique involving voice comparison evidence?

Lead Researchers

Brandon L. Garrett J.D.
William E. Crozier, Ph.D.
Rebecca Grady, Ph.D.

Journal

Journal of Forensic Sciences

Publication Date

22 April 2020

Publication Number

IN 106 IMPL

THE HYPOTHESIS

Participants would place less weight on voice comparison testimony than they would on fingerprint testimony, due to cultural familiarity and perceptions.

Participants who heard error rate information would put less weight on forensic evidence — voting guilty less often — than participants who heard traditional and generic instructions lacking error rates.

Participants who heard likelihood ratios would place less weight on forensic expert testimony compared to testimony offering an unequivocal and categorical conclusion of an ID or match.

APPROACH AND METHODOLOGY

WHO

900 participants read a mock trial about a convenience store robbery with 1 link between defendant and the crime

WHAT

2 (Evidence: Fingerprint vs. Voice Comparison)
x 2 (Identification: Categorical or Likelihood Ratio)
x 2 (Instructions: Generic vs. Error Rate) design

HOW

Participants were randomly assigned to 1 of the 8 different conditions

After reading materials + jury instructions, participants decided whether they would vote “beyond-a-reasonable-doubt” that the defendant was guilty

KEY TAKEAWAYS FOR PRACTITIONERS

Laypeople gave more weight to fingerprint evidence than voice comparison evidence.

Fewer guilty verdicts arose from voice evidence — novel forensic evidence methods might not provide powerful evidence of guilt.

Fingerprint evidence reliability decreases when jurors learn about error rates.

Error rate information appears particularly important for types of forensic evidence that people may already assume as highly reliable.

Participants considering fingerprint evidence were more likely to find the defendant not guilty when provided instruction on error rates. When the fingerprint expert offered a likelihood ratio, the error rate instructions did not decrease guilty verdicts.

When asked to rate which is worse — wrongly convicting an innocent person or failing to convict a guilty person or both — the study found the majority of participants were concerned with convicting an innocent person.

30 %

Participants who believe convicting an innocent person was the worst offense were less likely to vote guilty due to more doubt in the evidence.

0 %

Those who had greater concern for releasing a guilty person were more likely to vote guilty.

0 %

of participants believed the errors were equally bad.

Researchers found, overall, that presenting an error rate moderated the weight of evidence only when paired with a fingerprint identification.

FOCUS ON THE FUTURE

To produce better judicial outcomes when juries are formed with laypeople:

Direct efforts toward offering more explicit judicial instructions.

Craft a better explanation of evidence limitations.

Consider the findings when developing new forensic techniques –– new techniques aren’t as trusted by a jury despite proving more reliable and lowering error rates.

Pay attention to juror preconceptions about the reliability of evidence.

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Author: Molly Doolittle

INSIGHT

Error Rates, Likelhood Ratios, and Jury Evaluation of Forensic Evidence

OVERVIEW

Lead Researchers

Journal

Publication Date

Publication Number

THE HYPOTHESIS

APPROACH AND METHODOLOGY

WHO

WHAT

HOW

KEY TAKEAWAYS FOR PRACTITIONERS

Laypeople gave more weight to fingerprint evidence than voice comparison evidence.

Error rate information appears particularly important for types of forensic evidence that people may already assume as highly reliable.

When asked to rate which is worse — wrongly convicting an innocent person or failing to convict a guilty person or both — the study found the majority of participants were concerned with convicting an innocent person.

FOCUS ON THE FUTURE

To produce better judicial outcomes when juries are formed with laypeople:

Download

FULL Study

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INSIGHTS

Comparison of three similarity scores for bullet LEA matching

OVERVIEW

Lead Researchers

Journal

Publication Date

Publication Number

THE GOALS

The Study

1

Random Forest (RF):

2

Cross-Correlation (CC):

3

Consecutive Matching Striae (CMS):

Results

The Equal Error rate of each scoring method across multiple studies

FOCUS ON THE FUTURE

Additionally, explore relevant publications:

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FULL Study

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