siliconchip.com.au Australia’s electronics magazine April 2019 15the development of sufficiently fast and cheap computers
in the last 15-20 years or so that these systems have be-
come practical and commonplace.
It has also been necessary to develop appropriate com-
puter algorithms to perform the task of facial recognition.
This is an ongoing task.
Facial recognition involves one of the most challenging
problems in computing and artificial intelligence, which is
visual pattern recognition. This is something that humans do
easily and intuitively – it is built into our brains from birth.
We can easily recognise a familiar face, even with only
a partial, non-frontal view under poor lighting conditions
for a very brief moment.
But that is a difficult task for a machine.Early photograph-based systems
Facial recognition of sorts has origins back to the time
when cameras became widely available, around 1839.
Prisoners in Belgium were photographed as early as
1843 and in some parts of England, prisoners were pho-
tographed from 1848, so that they could be more easily
found if they escaped.
The Pinkerton National Detective Agency, a private de-
tective agency established in the USA in 1850 (and stillin existence), also photographed people it apprehended.
At the time, the alternative to a photograph (which too
had its critics in Victorian society) was to brand certain
convicted criminals who had committed serious offences.
Otherwise, it was tough to identify known criminals.
Before photographs, this was usually done by written de-
scriptions or direct testimony of victims or police.
For a discussion on photographing prisoners, see
siliconchip.com.au/link/aanb
Alphonse Bertillon was a French police officer and ear-
ly biometrics researcher who invented a system of physi-
cal measurements to enable police to identify a criminal
objectively.
He also developed the “mug shot”, the technique for
which was standardised in 1888.
Bertillon noted the difficulty in searching a collectionFig.1: a RAND tablet from the 1960s which allowed the human operator to input facial landmarks into a computer
database. The digitising surface was approximately 25cm x 25cm with one million possible locations. One operator could
process about 40 photos per hour. Little was published on this work, due to it having been funded by the US Government
(DARPA). It also had other uses, as seen in this photo. (siliconchip.com.au/link/aanf)
Google reverse image search
If you have a link to an image online or a saved copy of that
image, Google can often find other exact or similar copies of
that picture online and also possibly identify the people in the
image. Go to https://images.google.com/, click on the camera
icon and use “&imgtype=face” in the query.