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An Improved Algorithm for Gray Image Matching |
Xigao Shao, Kun Wu, Xiangbin Duan |
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Abstract During the process of analyzing the image matching principle, we
find that reducing the size of template images' searching space in
reference images and reducing the correlation calculation between
template images and sub-images can reduce the total amount of
calculation of the matching process. A new matching algorithm is
designed for the image matching process. The reference image is
preprocessed first; then sample the preprocessed reference image
with the normalized gray value as probability density; next the
rough matching points will be obtained by selecting proper sets of
sub-images and updating threshold dynamically; and lastly the
process of fine matching is executed. Least-squares method is used
to obtain the stationary point of quadratic curve in the nine
points' neighborhood with matching points as center, which is the
exact matching point eventually. By this way, the complexity of the
new algorithm is reduced. The experimental results show that the new
algorithm has certain superiority and practicability.
DOI: 10.12733/jics20101696
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