Papers › Fast and robust template matching with majority neighbour similarity and annulus...
Fast and robust template matching with majority neighbour similarity and annulus projection transformation
Jinxiang Lai, Liang Lei, Kaiyuan Deng, Runming Yan, Yang Ruan, Zhou Jinyun
In the paper, a novel fast and robust template matching method named A-MNS based on Majority Neighbour Similarity (MNS) and the annulus projection transformation (APT) is proposed. Its essence is the MNS, a useful, rotation-invariant, low computational cost and robust similarity measurement. The proposed method is theoretically demonstrated and experimentally evaluated as being able to estimate the rotation angle of the target object, overcome challenges such as background clutter, occlusion, arbitrary rotation transformation, and non-rigid deformation, while performing fast matching. Empirical results evaluated on the up-to-date benchmark show that A-MNS is 4.419 times faster than DDIS (the state-ofthe-art) and is also competitive in terms of its matching accuracy.
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