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Abstract
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Article Information:
Idle Object Detection in Video for Banking ATM Applications
K. Kausalya and S. Chitrakala
Corresponding Author: K. Kausalya
Submitted: March 18, 2012
Accepted: April 06, 2012
Published: December 15, 2012 |
Abstract:
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This study proposes a method to detect idle object and applies it for analysis of suspicious events.
Partitioning and Normalized Cross Correlation (PNCC) based algorithm is proposed for the detection of moving
object. This algorithm takes less processing time, which increases the speed and also the detection rate. In this
an approach is proposed for the detection and tracking of moving object in an image sequence. Two consecutive
frames from image sequence are partitioned into four quadrants and then the Normalized Cross Correlation
(NCC) is applied to each sub frame. The sub frame which has minimum value of NCC, indicates the presence
of moving object. The proposed system is going to use the suspicious tracking of human behaviour in video
surveillance and it is mainly used for security purpose in ATM application. The suspicious object’s visual
properties so that it can be accurately segmented from videos. After analyzing its subsequent motion features,
different abnormal events like robbery can be effectively detected from videos. The suspicious action in ATM
are many, such as using mobile phones, multiple persons trying to access the ATM machine in same time,
kicking of each other, idle object and it shows event corresponding to Vandalism and robbery. In proposed
system, idle object detection is used to identify by using PNCC algorithm with P-filter (Particle) and by
extracting the features of the object in an enhanced way by using the curvelet based transformation.
Key words: Cross correlation, detection, motion tracking, moving object, normalized, suspicious action,
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Cite this Reference:
K. Kausalya and S. Chitrakala, . Idle Object Detection in Video for Banking ATM Applications. Research Journal of Applied Sciences, Engineering and Technology, (24): 5350-5356.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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