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Biometrics - News

MorphoTrak tattoo recognition algorithm NIST Tatt-C evaluation

Published on 5 August, 2015
The MorphoTrak algorithm successfully found different instances of the same tattoo on the same subject

MorphoTrak's tattoo recognition algorithm helps make the transition from keyword to automated search

MorphoTrak, a U.S. subsidiary of Morpho (Safran), announced recently that MorphoTrak's tattoo recognition algorithm placed first in the Tattoo Recognition Technology - Challenge (Tatt-C) evaluation conducted by the National Institute of Standards and Technology (NIST).

Trial examination

Each trial examined a critical aspect of performance for an automated tattoo recognition solution. In the identification trials, the MorphoTrak algorithm successfully found different instances of the same tattoo on the same subject, collected over time. MorphoTrak also excelled at finding a small region of interest within a larger tattoo, as well as determining whether an image contained a tattoo.

Tattoo images have traditionally been regarded as a soft biometric -- that is, visual information that can be used to narrow down the range of candidates for identification and investigation, but cannot be used to explicitly identify an individual. Law enforcement organisations have been collecting tattoo images as long as they have been collecting mugshots, and while mugshots can now be submitted for automated searches using face recognition algorithms, tattoos are still categorised by text, in broad categories such as "Dragon," and "Skull." The team that developed MorphoTrak's tattoo recognition algorithm wants to help law enforcement make the transition from keyword search to automated search of tattoo images, much in the same way we now search for fingerprints and faces.

Automated tattoo recognition solution

Celeste Thomasson, President and CEO of MorphoTrak, stated, "MorphoTrak is proud to continue its tradition of leadership and commitment to excellence in the field of biometric technology. Prior to MorphoTrak's work in this area, investigators had to rely on text keywords to find tattoos that were similar in appearance. Our continuously improving tattoo recognition algorithm takes the criminal justice, forensic investigation and public security communities one step closer to a high-performance automated tattoo recognition solution."

Dr. Peter Lo, MorphoTrak Senior Research Manager, will present a session on Tattoo Recognition, including commentary on the NIST Tatt-C benchmark test, at the 2015 International Association of Identification (IAI) on Wednesday, August 5, 7:30 a.m. - 8:30 a.m.

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