Digital image correlation as a tool for surface deformation measurement has been widely used in the field of
experimental mechanics. The method is known to resolve deformation gradient fields with sub-pixel accuracy. In this
paper, we address the application of digital image correlation to the image location with sub-pixel accuracy to estimate
displacement of multiple frames of video sequences. The estimation effect depends on various factors such as image
noise and the correlation algorithm chosen. Algorithms of the
sub-pixel location on image are analyzed: Gray-value
Interpolation based Image Correlation and Correlation Coefficient Distribution based Fitting. However, Gray-value
Interpolation needs a large amount of computational consumption although has high accuracy and it is apt to be
influenced by noisy. Correlation Coefficient Distribution has low accuracy but high effective performance. According to
the characteristics of these algorithms, a mix algorithm is introduced to improve both accuracy and computational
consumption. The imaging process and algorithm execution are simulated using MATLAB. Further more, we could
evaluate the displacements of moving objects between two frames of real video sequences and obtain the reconstructed
images through displacement data. The validity of the mixed image location algorithm is obviously verified by
comparison between original frames and reconstructed image.
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