| Paper Details: | Downloads: 501 |
| Serial Number: | P1150828002
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| Title: | A Novel approach to Detect and Track Moving Object using Partitioning and Normalized Cross Correlation
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| Authors: | Manoj S. Nagmode and Madhuri A. Joshi and Ashok M. Sapkal
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| Abstract: | Detection and tracking of moving objects in video
sequences can offer significant benefits to video
retrieval. Research in motion analysis has evolved over
the years as a challenging field, such as traffic
monitoring, military, medicine and biological sciences
etc. A novel approach is proposed for the detection and
tracking of moving object in image sequence. In this,
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. Next
step is to identify the location of the moving object.
Location of the moving parts is obtained by performing
some component connected analysis and
morphological processing. After that the centroid
calculation is used to track the moving object.
Number of experiment are performed using indoor and
outdoor image sequences. The results are compared
with simple difference and background subtraction
methods. The proposed algorithm gives better
performance in terms of detection Rate (DR) and
processing time per frame.
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| Keywords: | Normalized Cross Correlation, moving
object detection, Component Connectivity, Centroid,
Tracking, Processing time, Detection Rate, False
Alarm Rate.
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| Journal/Conference: | International Journal of Graphics, Vision and Image Processing
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| Volume: | 9
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| Issue: | 4
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| Submission Date: | 7/9/2008 12:00:00 AM
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| Review Date: | 12/18/2008 12:00:00 AM
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| Publishing Date: | 7/2/2009 12:00:00 AM
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| Article Downloads: | 501
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