Virtually recomposing destroyed frescoes is of great importance for heritage conservation. Given a digitized fresco image and a digitized set of fragments, such a problem is challenging due to the potentially large number of fragments, their irregular shape, uniqueness and non-overlapping constraints, the possible absence of fragments and the possible presence of small, homogeneous, eroded and/or spurious fragments. To cope with these specific features, we propose in this paper a fast and efficient non-dense approach benefiting from previous developments in pattern matching. Preliminary experiments led on simulations exhibit a mean accuracy above 90% with a mean translation error of less than 4 pixels and a mean orientation error of about 1 degree. An analysis of fresco and fragment features impacting the algorithm is also provided. Compared to a dense approach and the recent DeepMatch approach, the proposed one remains competitive both in running time and accuracy.

实际上，对损毁的壁画进行重组对于遗产保护非常重要。给定数字化的壁画图像和数字化的片段集，由于可能存在大量的片段，它们的不规则形状，唯一性和不重叠的约束，可能缺少片段以及可能存在小的，均匀的片段，因此该问题具有挑战性，侵蚀和/或伪造的碎片。为了应对这些特定功能，我们在本文中提出了一种快速有效的非密集方法，该方法得益于模式匹配的先前发展。在模拟的基础上进行的初步实验显示平均精度高于90％，平均平移误差小于4像素，平均方向误差约为1度。还提供了影响该算法的壁画和碎片特征的分析。