New Tool Could Link Serial Killer Victims by Facial Similarities

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A stylized diagram to illustrate the 21-point landmarks (red circles) and the 19 pixel count measurements. Credit: Murdoch University via Chapman, B., Keatley, D., Coumbaros, J., & Maker, G. (2026). Development of face similarity linkage for the attribution of intelligence links in unsolved sexually motivated serial homicide. The Police Journal: Theory, Practice and Principles, 0(0).

Researchers at Murdoch University have developed a forensic intelligence tool that could help police link the victims of serial offenders by analyzing their facial appearance.

Previous studies have shown that features such as age, sex, class and physical appearance can influence an offender’s choice of victim. It is also suspected that some serial killers seek out victims who resemble an opposite sex parent or a family member associated with childhood trauma.

“Serial homicide and sexual offenders are sometimes linked to many more offences than they are formally charged with,” said Associate Professor Brendan Chapman, Chair in the School of Medical, Molecular and Forensic Sciences at Murdoch University. “Cases without powerful evidence often remain unsolved or unlinked and go cold. A new method that could help link victims to victims, through subtle facial geometry similarities, may provide intelligence to help investigators focus their efforts.”

Led by Chapman, researchers explored Face Similarity Linkage (FSL) as a forensic tool to help identify potential connections between victims of sexually motivated crime.

The team analyzed photos of three people from a public research image database, each photographed at nine different angles—replicating the kind of informal, off‑angle images often supplied to police from social media or personal collections.

They then isolated 21 key facial landmarks—including the corners of the eyes, edges of the lips, chin and nose tip — measured the distances between them, and converted those measurements into ratios. This allowed the team to cancel out distortions caused by photo angle or scale and compare faces more reliably.

Using several tests to minimize variation between readers and camera angles, the researchers identified which facial measurements were most useful in distinguishing between the three unrelated individuals.

According to the study, published in The Police Journal: Theory, Practice and Principles, the team found 55 facial measurements that remained stable across different angles, allowing them to compare faces far more reliably than before. The measurements could be used to find differences or similarities in the facial structure of victims, even with imperfect photos.

“With only simple instructions, our untrained testers were still able to keep error rates to around 5%, and we know we can drive that even lower with proper training,” said Chapman.

The tool also has the potential to be automated with artificial intelligence.

“We were quite deliberate in developing the technique to be easily adopted by investigators without the need for expensive or proprietary programs, however we’ve opened the door for AI to take it even further,” said Chapman. “An automated system could screen large numbers of victim images quickly and reliably, giving investigators valuable leads in cases where evidence is scarce. While this technique will never replace DNA evidence, it can flag potential links between victims in cases where DNA doesn’t exist or has degraded. It gives investigators a new starting point.”

Republished courtesy of Murdoch University



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