Experimental Analysis of Performance Comparison on Both Linear Filter and Bidirectional Con dential Technique for Spatial Domain Optical Flow Algorithm
Experimental Analysis of Performance Comparison on Both Linear Filter and Bidirectional Con dential Technique for Spatial Domain Optical Flow Algorithm
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2013
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eng
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application/pdf
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12 pages
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ECTI Transactions on Computer and Information Technology Vol. 7, No. 2 (November 2013), 156-167
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Abstract
Optical flow is a method for classifying the density
velocity or motion vector (MV) in a degree of pixel
basis for motion classification of image in video sequences.
In actual situation, many unpleasant situations
usually generate noises over the video sequences.
These unpleasant situations corrupt the performance
in efficiency of optical flow. In turn to increase the
efficiency of the MV, this research work proposes the
performance comparison on linear filter and bidirectional
confidential technique for spatial domain optical
flow algorithms. Our experiment concentrates
on the 3 classical spatial based optical flow algorithms
(such as spatial correlation-based optical flow
(SCOF), Horn-Schunk algorithm (HS) and Lucas-
Kanade algorithm (LK)). Different standard video
sequences such as AKIYO, CONTAINER, COASTGUARD,
and FOREMAN are comprehensively evaluated
to demonstrate the effectiveness results. These
video sequences have differences in aspect of action
and speed in foreground and background. These
video sequences are also debased by the Additive
White Gaussian Noise (AWGN) at different noise degree
(such as AWGN at 25 dB, 20 dB, and 15 dB
consequently). Peak Signal to Noise Ratio (PSNR) is
utilized as the performance index in our observation.