Dr. Atheer A. Sabri; Hamsa D. Majeed
Volume 13, Issue 1 , April 2013, , Page 32-40
Abstract
Abstract–The estimation of optical flow is the basic step for many engineering
applications that exploit the image processing field as a part of their models. In this
paper a model called Slantlet Based Optical Flow Estimation (SLT_OFE) is proposed to
estimate the optical flow. Slantlet Transform ...
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Abstract–The estimation of optical flow is the basic step for many engineering
applications that exploit the image processing field as a part of their models. In this
paper a model called Slantlet Based Optical Flow Estimation (SLT_OFE) is proposed to
estimate the optical flow. Slantlet Transform (SLT) used as an effective tool, 2D and
3D- SLT- Level 2 (SLT2) are computed and employed in the proposed model to provide
high accuracy estimation of the optical flow. By its definition, optical flow is a velocity
field, so the velocities in this paper are computed using the widely used Differential
Technique. Two methods from this technique are adopted; Horn-Schunck Method and
Lucas-Kanade Method. The optical flow is estimated for two types of image sequences;
synthetic sequences and real sequences. Unlike the real sequences, the synthetic
sequences have known true velocities which are used for evaluating the proposed model
by calculating mean error (Mean Err.), angular error (Ang. Err.) and Standard Deviation
(STD). For extreme study of its performance, the proposed SLT_OFE is compared with
three other models that are based on level two (Discrete Wavelet Transform (DWT),
Discrete Multi Wavelet Transform (DMWT) and Framelet Transform (FT) ) which are
implemented in this paper and employed in the conventional models, 2D-DWT2_OFE,
2D-DMWT2_OFE and 2D-FT2_OFE. The results show that the proposed model offers
minimum values in errors and STD when 2D-SLT2 is used, and these results are
improved by using 3D-SLT2. This leads to the fact that the proposed model SLT_OFE
through both of 2D and 3D approaches possesses an improvement in the optical flow
estimation process with higher accuracy, than the other models produced in the same
circumstances. MATLAB Version 7.12 (R2011a) is used to implement the proposed
model and the conventional models.
