Data mining is the application of statistical techniques and programmatic algorithms to discover previously unnoticed
relationships within the data. Video surveillance has long been in use to monitor security sensitive areas such as banks, department
stores, highways, crowded public places and borders. The advance in computing power, availability of large-capacity storage devices
and high speed network infrastructure paved the way for cheaper, multi sensor video surveillance systems. The ultimate goal of the
present generation surveillance systems is to allow video data to be used for on-line alarm generation to assist human operators and
for offline inspection effectively. Moving object detection is the basic step for further analysis of video.
Published In:IJCSN Journal Volume 6, Issue 3
Date of Publication : June 2017
Pages : 356-361
Tables : --
Avinash P. Ingle : has completed his BE in IT from Government
college of engineering Amaravti. He has completed his M.Tech
in CSE from GHRCE Nagpur. He is a Assistant Professor at
Department of Information Technology in Priydarshini Institute of
Engineering and Technology, Nagpur. His research interests are
Data Mining, Data Structure, Image Processing artificial
Sushma D. Ghode : has completed her B.E. in Information
Technology in 2005 and M.E. in Wireless Communication and
Computing in 2010, both from GHRCE Nagpur, under RTM
Nagpur University. She is pursuing PhD from dept. of
Information Technology YCCE, Nagpur. She is presently
working as assistant Professor in Dept. of Computer Science
and Engineering at MIT Aurangabad (India).
Data Mining; Video surveillance; Object detection
The hill climbing algorithm will effectively find out the
abnormal activities. It includes target area detection,
video segmentation and clustering. Hill climbing can
often produce a better result than other algorithms such purpose.
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