Abstract: The aim of this research is to analyze humans fingerprint texture in order to determine their Age & Gender, and correlation of RTVTR and Ridge Count on gender detection. The study is to analyze the effectiveness of physical biometrics (thumbprint) in order to determine age and gender in humans. An application system was designed to capture the finger prints of sampled population through a fingerprint scanner device interfaced to the computer system via Universal Serial Bus (USB), and stored in Microsoft SQL Server database, while back-propagation neural network will be used to train the stored fingerprint. The specific Objectives of this research are to: Use fingerprint sensor to collect different individual fingerprint, alongside their age and gender, Formulate a model and develop a fingerprint based identification system to determine age and gender of individuals and evaluate the developed system.

E O Omidiora, O. Ojo, N.A. Yekini and T.O. Tubi, “Analysis, Design and Implementation of Human Fingerprint Patterns System “Towards Age & Gender Determination, Ridge Thickness To Valley Thickness Ratio (RTVTR) & Ridge Count On Gender Detection” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(2), 2012. http://dx.doi.org/10.14569/IJARAI.2012.010210

@article{Omidiora2012,
title = {Analysis, Design and Implementation of Human Fingerprint Patterns System “Towards Age & Gender Determination, Ridge Thickness To Valley Thickness Ratio (RTVTR) & Ridge Count On Gender Detection},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2012.010210},
url = {http://dx.doi.org/10.14569/IJARAI.2012.010210},
year = {2012},
publisher = {The Science and Information Organization},
volume = {1},
number = {2},
author = {E O Omidiora and O. Ojo and N.A. Yekini and T.O. Tubi}
}