A team of engineers at the University of Ilorin
has produced a prototype biometric machine that
is capable of eliminating a major deficiency
encountered by imported machines. The team leader, Prof. Tunji Samuel Ibiyemi of the
Electrical and Electronics Engineering Department,
said that with the use of local content, the
researchers have been able to unravel the
challenge of the inability of the imported
biometric machine to adequately recognise physical features of black people. Prof. Ibiyemi disclosed that imported solutions to
the challenges of impersonation, economic fraud,
multiple voting, examination malpractices,
election rigging, and security challenge do not
work optimally among black people as they do
among white people, adding that “what we have just produced one that works better for blacks.” The don, whose research effort was sponsored
by the World Bank-assisted Science and
Technology Education Post-Basic (Step-B) Project,
explained that “this lack of local content in the
making of the machines we use for vital national
assignments perhaps explain why government efforts on projects like e-voting, national identity
card scheme, security intelligence on criminal
citizens had not been yielding enough fruits.” Prof. Ibiyemi led a team of three other
researchers, Prof. J. Sadiku of Computer Science
Department, Dr. S. A. Aliu and Dr. I. O. Avazi of
Electrical and Electronics Engineering Department,
to study ‘Biometric Signal Processing for Personal
Application and Forensic Application’. The Professor of Electrical and Electronics
Engineering said, “An average Chinese recognises
Chinese people more easily. Likewise, Americans
know one another better. When I was in Britain,
any black person could pick any of his friend’s
identity card and go anywhere across the country unfettered. Those working at the
airports will confirm to you that you need local
people to identify one another. “Most imported machines don’t recognise tribal
marks. These machines raise alarm when they
see a masked face. But what we have produced
can recognise tribal marks, faces that are masked
and faces that are disguised using cosmetics.” Prof. Ibiyemi pointed out that the machines
developed by his team are not only more cost-
effective than their imported equivalents, they
are also more functionally efficient. He said, “For
instance, after our proposal was approved for
funding and we were experiencing delays in accessing the money, we funded the
development of a locally made Iris Scanner at
N60, 000. But when we eventually got money to
buy this equipment, we got it for N400, 000 (that
is 2,500 US dollars). And the former produces
sharper and clearer images than the latter.” He explained further, “Besides this, we used
machines (computers) to recognise the human
face, human iris, finger prints, toe prints and sole
prints. We worked on speaker and speech
recognition, signature verification and hand
writing verification. “What we found is amazing. For example, using
any of these parameters, we can get different
patterns of iris, fingerprints, toeprints, soleprints
that differentiate the 14 billion people in the
world. No two persons have the same pattern for
any of these parameters. In fact, the left iris pattern for an individual is different from the
right side for the same individual. Similarly, the
thumb print is different from the index
fingerprint for each person and so on. “No website is available within Africa for
biometric data on black people. Foreign data are
populated by white people. We needed black
people’s data to work with, so we started our
own website-www.unilorin.edu.ng/step-b/
biometrics. “We collected over one million fingerprints,
600,000 toeprints, 200 soleprints, and 374 latent
fingerprints. The website is hosted in Italy. We
also went to the home of lepers and took 200
soleprints. When we brought them to the
laboratory, we discovered that it is easier to recognise people through their soleprints than
through their fingerprints. “Our fingerprint equipment will identify each
individual. We can detect multiple voting. There
are five groupings of finger prints. Using one
million samples, we compared our result with US-
based Federal Bureau of Intelligence (FBI) result,”
he said.
sources: tribune.com.ng/news2013/index.php/en/component/k2/item/22999-unilorin-dons-break-major-biometric-machine-riddle.html

Can you see now?Our own engineers have produced a better equipment for the world.But Nigerians don't recognise our universities and their research work.