Closed-loop feedback registration for consecutive images of moving flexible targets

Applied Intelligence(2022)

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摘要
Advancement of imaging techniques enables consecutive image sequences to be acquired for quality monitoring of manufacturing production lines. Registration for these image sequences is essential for in-line pattern inspection and metrology, e.g., in the printing process of flexible electronics. However, conventional image registration algorithms cannot produce accurate results when the images contain duplicate and deformable patterns in the manufacturing process. Such a failure originates from the fact that the conventional algorithms only use spatial and pixel intensity information for registration. Considering the nature of temporal continuity of the product images, in this paper, we propose a closed-loop feedback registration algorithm. The algorithm leverages the temporal and spatial relationships of the consecutive images for fast, accurate, and robust point matching. The experimental results show that our algorithm finds about 100% more matching point pairs with a lower root mean squared error and reduces up to 86.5% of the running time compared to other state-of-the-art outlier removal algorithms.
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关键词
feedback registration,image sequence registration,point pattern matching (PPM),scale-invariant feature transform (SIFT)
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