The Nipple-Areola Complex for Criminal Identification

TL;DR

This paper explores the potential of using the nipple-areola complex (NAC) as a biometric feature for criminal identification, especially when facial features are obscured, and introduces a new dataset for this purpose.

Contribution

It presents the first study on NAC-based identification and provides a new dataset, NTU-Nipple-v1, for research in this area.

Findings

NAC features can aid in offender identification.

Deep learning methods show promising results on the dataset.

The dataset contains 2732 images of 428 individuals.

Abstract

In digital and multimedia forensics, identification of child sexual offenders based on digital evidence images is highly challenging due to the fact that the offender's face or other obvious characteristics such as tattoos are occluded, covered, or not visible at all. Nevertheless, other naked body parts, e.g., chest are still visible. Some researchers proposed skin marks, skin texture, vein or androgenic hair patterns for criminal and victim identification. There are no available studies of nipple-areola complex (NAC) for offender identification. In this paper, we present a study of offender identification based on the NAC, and we present NTU-Nipple-v1 dataset, which contains 2732 images of 428 different male nipple-areolae. Popular deep learning and hand-crafted recognition methods are evaluated on the provided dataset. The results indicate that the NAC can be a useful characteristic for offender identification.