Tattoo Recognition System is coming! Recently committed a crime? Do you happen to have a large visible tattoo? Then you could soon be tracked down simply by the body art on your skin, the NIST has suggested.

The National Institute of Standards and Technology is working on an algorithm that will essentially be able to distinguish law breakers by the tattoos that they sport.

This step forward in law enforcement could be seen as backlash from a result of the London riots in 2011, where similar technology was used to try and track down rioters who wished to try and conceal their identity whilst wreaking havoc throughout parts of the capital.

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The main challenges that law enforcement, and subsequently the NIST, faced with the existing technology was that the existing software lacked consistency. This was highlighted further when suspects had similar markings on their extremities. The institute was quoted as saying that the increasing variety of tattoo designs requires multiple keywords, and examiner subjectivity can lead to the same tattoo being labelled differently depending on the examiner.”

This main obstacle ignited the development of an automated image-based tattoo matching technology, with the FBI Biometric Center of Excellence (BCOE) spearheading the project, the result of which would have drastically more consistent results if successful.

Scientist Mei Ngan came up with the idea that a better quality of collected images was needed in order to achieve the desired results, and suggested that recognising an image of a tattoo from a sketch or other sources other than a photo would increase the chance of tattoo detection for the software, and when paired with the objective of collected more high-quality images, the recognition accuracy should follow suit.

sourceNIST

Waqas

Waqas Amir is a Milan-based cybersecurity journalist with a passion for covering latest happenings in cyber security and tech world. In addition to being the founder of this website, Waqas is also into gaming, reading and investigative journalism.