Abstract:
Biometric as an identification tool for children recognition is started in the late 19th century by Sir Galton. However, it is
still in the developing stage even after the span of two centuries. The main hurdles in this process are the small size, non-uniform
growth of different biometrics and lack of public databases of children biometrics. The authors have touched all the aspects of fingerprint
recognition of children. Childhood is very important and crucial in the life of human beings. Most important vaccinations are given in
these years. Children are not able to take care of themselves therefore swapping, abduction and missing happens in this age. The main
objective is to reveal the progression study of children’s recognition for the age group of 0 to 5 years. The combination of transform
domain features and machine learning classifiers gives good accuracy of identification of children. Also, multimodal fusion and deep
learning approach will increase the identification accuracy of the children.In this paper, a complete survey of studies done for children
recognition using physiological biometric is covered. Detailed discussion on database availability, scanning devices, feature extraction
techniques, growth models used and matching algorithms is presented. Fingerprint modality is explored using their trends and challenges.
Also, the effectiveness of fingerprint modality for recognition of children is discussed.
