Large Scale Data Collection of Tattoo-Based Biometric Data from Social-Media Websites

Abstract

The use of tattoos as a soft biometric is increasing in popularity among law enforcement communities. There is great need for large scale, publicly available tattoo datasets that can be used to standardize efforts to develop tattoo-based biometric systems. In this work, we introduce a large tattoo dataset (WVU-MediaTatt) collected from a social-media website. Additionally, we provide the source links to the images so that anyone can re-generate this dataset. Our WVU-MediaTatt database contains tattoo sample images from over 1,000 subjects, with two tattoo image samples per subject. To the best of our knowledge, this dataset is significantly bigger than any current released publicly available tattoo dataset, including the recently released NIST Tatt-C dataset. The use of social media in deep learning, data mining, and biometrics has traditionally been a controversial issue in terms of data security and protection of privacy. In this work, we first conduct a full discussion on the issues associated with data collection from social media sources for the use of biometric system development, and provide a framework for data collection. In this study, within the process of creating a new large scale tattoo dataset, we consider the issues and make attempts protect the subject's privacy and information, while ensuring that subjects remain in control of their data in this study and the use of the data adheres to the guidelines proposed by the Heath Care Compliance Association (HCCA) and the U.S. Department of Health & Human Services.