Abstract:
Biometric systems have been using physiological & behavioral traits of humans
for the identification or verification of an individual. Most biometric systems have
been developed for adults in several applications particularly, in civilian and forensic
domains. There is a lack of well-defined systems for infant identification or
verification, and newborn recognition has got attention in recent years. There are
several applications that have a requirement to use of infant recognition particularly,
infant tracking, identifying a missing child, child swapping, etc. It is observed that
image acquisition for infant biometric systems does not follow the same
procedures as for adults. Since infants have different laying positions, acquiring face,
fingers and eye-related biometric is difficult. However, footprints can be easily
collected using some mobile-based devices even if the infants are in sleeping
positions. When dealing with such images, applying enhancement filters without
affecting the image quality is a crucial step. In this work, the quality of acquired
images is comparatively evaluated. A set of enhancement filters have experimented
with original and enhanced images, and the quality of images is measured using
image quality metrics. From the analysis, the Jerman enhancement filter and unsharp
masking show better-quality preservation and slight improvement in
performance with infant footprint biometric system.
