This paper presents a generic pre-processor for expediting
conventional template matching techniques. Instead of locating the
best matched patch in the reference image to a query template via
exhaustive search, the proposed algorithm rules out regions with no
possible matches with minimum computational efforts. While working
on simple patch features, such as mean, variance and gradient, the
fast pre-screening is highly discriminative. Its computational
efficiency is gained by using a novel octagonal-star-shaped template
and the inclusion-exclusion principle to extract and compare patch
features. Moreover, it can handle arbitrary rotation and scaling of
reference images effectively, and also be robust to uniform
illumination changes. GPU-aided implementation shows great efficiency
of parallel computing in the algorithm design, and extensive
experiments demonstrate that the proposed algorithm greatly reduces
the search space while never missing the best match. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22323 |
| Date | January 2017 |
| Creators | Liu, Bolin |
| Contributors | Wu, Xiaolin, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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