  Criminal and victim identification based on crime scene images is an
important part of forensic investigation. Criminals usually avoid
identification by covering their faces and tattoos in the evidence images,
which are taken in uncontrolled environments. Existing identification methods,
which make use of biometric traits, such as vein, skin mark, height, skin
color, weight, race, etc., are considered for solving this problem. The soft
biometric traits, including skin color, gender, height, weight and race,
provide useful information but not distinctive enough. Veins and skin marks are
limited to high resolution images and some body sites may neither have enough
skin marks nor clear veins. Terrorists and rioters tend to expose their wrists
in a gesture of triumph, greeting or salute, while paedophiles usually show
them when touching victims. However, wrists were neglected by the biometric
community for forensic applications. In this paper, a wrist identification
algorithm, which includes skin segmentation, key point localization, image to
template alignment, large feature set extraction, and classification, is
proposed. The proposed algorithm is evaluated on NTU-Wrist-Image-Database-v1,
which consists of 3945 images from 731 different wrists, including 205 pairs of
wrist images collected from the Internet, taken under uneven illuminations with
different poses and resolutions. The experimental results show that wrist is a
useful clue for criminal and victim identification. Keywords: biometrics,
criminal and victim identification, forensics, wrist.
