MorphoTrak announced the acquisition of a tattoo matching technology developed by Michigan State University (MSU). With this innovative technology, the corrections and law enforcement community will now have the capability to accurately and efficiently search tattoo image databases to identify suspects, criminals and victims. This content-based image retrieval and matching technology uses features such as color, shape, and texture present in tattoo images instead of labels or keywords, to compute the similarity between images.
MorphoTrak announced the acquisition of a tattoo matching technology developed by Michigan State University (MSU). With this innovative technology, the corrections and law enforcement community will now have the capability to accurately and efficiently search tattoo image databases to identify suspects, criminals and victims. This content-based image retrieval and matching technology uses features such as color, shape, and texture present in tattoo images instead of labels or keywords, to compute the similarity between images.
"It's good to see this type of technology being made available to law enforcement agencies," said Peter Higgins of Higgins and Associates, International and Former Deputy Assistant Director in charge of the FBI's IAFIS program. "I have seen the initial successes achieved by the National Gang Targeting, Enforcement & Coordination Center, the National Gang Intelligence Center, and the National Capitol Region AFIS system in linking subjects via tattoos. With the increased awareness of the value of matching tattoos for suspect and victim identification as well as associating tattoos to particular gang affiliation, automatic image retrieval and indexing capabilities are likely to be integrated into the FBI's Next Generation Identification (NGI) system later in this decade to serve as another valuable tool for the criminal justice community."
"This technology is an invaluable tool to assist law enforcement with intelligence gathering for suspect and victim identification. We trust MorphoTrak to bring this technology to bear at all levels of the law enforcement community," said Anil Jain, University Distinguished Professor in the Department of Computer Science and Engineering at MSU. Jain has received multiple awards for his contributions and leads MSU's research in pattern recognition and biometrics.
"MorphoTrak understands the importance of joining forces with our nation's top academic institutions to help extend crime fighting capabilities with groundbreaking technologies," said Daniel Vassy, President and CEO of MorphoTrak.
According to a 2006 Pew Research Center survey, more than 36 percent of individuals between the ages of 18 to 40 have at least one tattoo. This proportion is much higher among criminals and members of criminal gangs. Consequently, federal, state and local law enforcement agencies have been collecting images of tattoos for many years. Although a tattoo alone cannot identify a person, this alternative trait provides valuable information that can help narrow the field and identify gang members.
A typical tattoo search involves matching a text description of the tattoo making the process slow and inaccurate. With image-based tattoo matching, agencies will now have the ability to more fully exploit their large repositories of tattoo images for the identification of suspects and victims. Tattoos are particularly important for criminal identification as they often contain subtle clues to a suspect's background and history, such as gang membership, previous criminal convictions, claims of criminal activity and number of years spent in jail.