Name
Kucherov Sergei Aleksandrovich
Scholastic degree
•
Academic rank
—
Honorary rank
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Organization, job position
South Federal University
Web site url
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Articles count: 1
One of the key areas of interdisciplinary research is to
ensure public safety. In order to solve a number of
problems within this area we can effectively use
information technology and, in particular, an
automated pattern recognition technology and
identification of objects on digital images. There are
addition problems in objects identifying process
besides eliminating the influence of ambient light,
angle, items of clothing and headgear. To ensure the
applicability of the recognition approach to public
security issues it must meet requirements of the high
processing speed, the replenishment capabilities onthe-fly
list of known images, and the low
computational complexity of algorithms. The article
deals with the main approaches to the recognition and
identification of objects on digital images based on
statistical approaches, as well as neural network
models. We have allocate their basic features and
principles, provided a brief description of each
method. Consideration has been made in terms of the
application for the problems of public safety, in which
there is importance of the speed of the identification of
the object, the ability of quickly learning for the
system to accept new images and simultaneously
process a plurality of input images. The analysis of the
existing approaches has shown that none of them
satisfy at least one or several needs, which are defined
by domain problems of public safety