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- W2018494041 abstract "Matching the template image in the target image is the fundamental task in the field of computer vision. Aiming at thedeficiency in the traditional image matching methods and inaccurate matching in scene image with rotation, illuminationand view changing, a novel matching algorithm using local features are proposed in this paper. The local histograms ofthe edge pixels (LHoE) are extracted as the invariable feature to resist view and brightness changing. The merits of theLHoE is that the edge points have been little affected with view changing, and the LHoE can resist not only illuminationvariance but also the polution of noise. For the process of matching are excuded only on the edge points, the computationburden are highly reduced. Additionally, our approach is conceptually simple, easy to implement and do not need thetraining phase. The view changing can be considered as the combination of rotation, illumination and sheartransformation. Experimental results on simulated and real data demonstrated that the proposed approach is superior toNCC(Normalized cross-correlation) and Histogram-based methods with view changing." @default.
- W2018494041 created "2016-06-24" @default.
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- W2018494041 date "2013-10-27" @default.
- W2018494041 modified "2023-09-27" @default.
- W2018494041 title "Template match using local feature with view invariance" @default.
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- W2018494041 doi "https://doi.org/10.1117/12.2031068" @default.
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