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A graph-based optimization algorithm for fragmented image reassembly

机译:基于图的碎片图像重组优化算法

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摘要

We propose a graph-based optimization framework for automatic 2D image fragment reassembly. First, we compute the potential matching between each pair of the image fragments based on their geometry and color. After that, a novel multi-piece matching algorithm is proposed to reassemble the overall image fragments. Finally, the reassembly result is refined by applying the graph optimization algorithm. We perform experiments to evaluate our algorithm on multiple torn real-world images, and demonstrate the robustness of this new assembly framework outperforms the existing algorithms in both reassembly accuracy (in handling accumulated pairwise matching error) and robustness (in handling small image fragments).
机译:我们提出了一种基于图的自动2D图像片段重组的优化框架。首先,我们根据图像片段的几何形状和颜色计算每对图像片段之间的电位匹配。之后,提出了一种新颖的多段匹配算法来重新组装整个图像片段。最后,通过应用图优化算法来优化重组结果。我们进行实验以评估在多个残缺真实世界图像上的算法,并证明此新组装框架的鲁棒性在重组精度(处理累积的成对匹配错误)和鲁棒性(处理小图像碎片)方面均优于现有算法。

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