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Tattoo Recognition Technology – Challenge (Tatt-C)

September 23, 2014: Tatt-C participation window now open/Dataset available!
Organizations interested in participating in Tatt-C should follow the steps described in the Participation in Tatt-C section of this website.

Scope

The Tattoo Recognition Technology – Challenge (Tatt-C) is being conducted to challenge the commercial and academic community in advancing research and development into automated image-based tattoo matching technology. The activity will assess the capability of image-based tattoo recognition algorithms to perform detection and retrieval of tattoos, with the goals to determine which algorithms are most effective and whether any are viable for the following operational use-cases: 1. Tattoo Similarity – matching visually similar or related tattoos from different subjects; 2. Tattoo Identification - matching different instances of the same tattoo image from the same subject over time; 3. Region of Interest - matching a small region of interest that is contained in a larger image; 4. Mixed Media - matching visually similar or related tattoos using different types of images (e.g. sketches, scanned print, computer graphics, or natural images); 5. Tattoo Detection - detecting whether an image contains a tattoo or not.

Interested Parties

Please contact NIST if:

a) You are a developer of tattoo matching algorithms or have an interest in developing such a capability.

b) You represent an organization possessing suitable tattoo datasets that might be valuable to our effort.

c) You have an operational interest or need for image-based matching of tattoo images.

Background

Tattoos have been used for many years to assist law enforcement in the identification of criminals and victims and for investigative research purposes. Tattoos provide valuable information on an individual’s affiliations or beliefs and can support identity verification of an individual. Historically, law enforcement agencies have followed the ANSI-NIST-ITL 1-2011 standard to collect and assign keyword labels to tattoos. This keyword labeling approach comes with drawbacks, which include the limitation of ANSI-NIST standard class labels to describe the increasing variety of new tattoo designs, the need for multiple keywords to sufficiently describe some tattoos, and subjectivity in human annotation as the same tattoo can be labeled differently between examiners. As such, the shortcomings of keyword-based tattoo image retrieval have driven the need for automated image-based tattoo recognition capabilities.

Structure of Tatt-C

Tatt-C is structured around problems that are designed to challenge the commercial and academic community in advancing research and development into automated image-based tattoo recognition technology. While some research and commercial capability is available, tattoo recognition is not a mature industry. There is no common test data and use cases to evaluate and develop systems for next generation government applications. To address this shortcoming, the Tatt-C dataset was developed as an initial tattoo test corpus that addresses use cases derived from operational scenarios provided by the FBI’s Biometric Center of Excellence (BCOE).

The Tatt-C dataset consists of still images of tattoos captured operationally by law enforcement agencies. The operational nature of this corpus imposes challenges on traditional image retrieval methodologies given the large variation in capture environment/process and tattoo content/quality. The following are examples of such challenges represented in the Tatt-C dataset:

  • Inconsistent image lighting and scale
  • Occlusions due to clothing and different image backgrounds
  • Different tattoo background or embellishments around primary tattoo content
  • Blended images or multiple tattoos in a single image
  • Inconsistent orientation of body/appendages and images
  • Extremely faded tattoos
  • Ambiguous or unfamiliar abstractions (difficult or impossible for different people to view and interpret consistently)

The Tatt-C dataset provides a basis for objectively measuring and comparing tattoo recognition capabilities, with partitions focused on but not limited to the following use cases:

  • Tattoo Similarity. What is the retrieval performance for finding visually similar or related tattoos from different subjects?
  • Tattoo Identification. What is the retrieval performance for finding different instances of the same tattoo image from the same subject over time?
  • Region of Interest. What is the retrieval performance for finding a small region of interest that is contained in a larger image?
  • Mixed Media. What is the retrieval performance for finding visually similar or related tattoos using different types of images (e.g. sketches, scanned print, computer graphics, or natural images)?
  • Tattoo Detection. What is the performance for detecting whether an image contains a tattoo or not?

Participation in Tatt-C

At a high level, participants of the challenge would obtain the dataset, run their algorithms against the specified partitions, and send their results back to NIST.

Organizations interested in participating in Tatt-C should follow the steps below:

Obtain the Tatt-C Dataset

  1. Fill out the Tatt-C Data Request Form and email it to tattc_dataset@nist.gov.
  2. After receipt of the request form, the submitter will receive, via email, a data release document that will need to be signed and further instructions on obtaining the dataset will be provided.

Download the Tatt-C Dataset, Concept, and Evaluation Plan

  1. The Tatt-C Dataset, Concept, and Evaluation Plan establishes the protocol that participants should follow for the Tatt-C activity, which includes detailed information regarding the dataset, the challenge problems and the output format for self-reporting back to NIST, and accuracy metrics used to assess performance.
  2. The first version of the document is available here.

Download sample supporting reference software

  1. Scoring (R script)
      • This script takes an output file and ground truth file in the formats specified by the Tatt-C Dataset, Concept, and Evaluation Plan and generates metrics described in the document.
      • The first version of the sample scoring script is available here.

Important Dates:

September 23, 2014 – February 6, 2015: Phase 1 participation window

February 7 – April 17, 2015: Phase 2 participation window

May 4, 2015: Registration deadline to attend Tatt-C workshop

June 2015: Tatt-C workshop at NIST

Contact Information:

For more information, please contact tattoo AT nist DOT gov.

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