Image inpainting is a challenging reconstruction of the damaged image in photography, especially for more valued artwork than before. The damages are mostly caused by scratches and worn out, so they can not be easily fixed physically. Thus, many scientists proposed sophisticated methods for restoring the damaged image into a new one similar to an original image. However, these methods have not solved the problem effectively if the missing region is large. In this paper, we focus on how to restore a large missing region in image inpainting. This algorithm is composed of two steps: structure propagation and color propagation. In structure propagation, we segment a large region (non-homogeneous) into several small regions (homogeneous) based on the salient structure of missing region. Then, we applied a simple pixel-based inpainting method called the Fast Marching Method (FMM) to fill in the missing homogeneous regions by color propagation. In the experimental section, we applied several kinds of missing regions, such as irregular and regular missing regions, in large sizes. The results show that our proposed method performs well in various conditions. INDEX TERMSImage inpainting, user interaction, structure propagation, color propagation, fast marching method (FMM).

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�Full-scale shaking table tests were carried out at E-Defense to evaluate the seismic performance of a traditional wooden residential structure. The specimen was a post-and-beam frame with a plan dimension of 5.91 × 11.82 m and height of 7.53m. A key feature of the specimen was the oversized beams and columns. The design seismic load resistance was provided entirely by mud plaster walls.The beam-to-column joints were achieved by an oak peg using no metal fasteners. Under BCJ-L2 shaking, the first story exhibited a story drift of 3.7%, and one of the corner columns cracked. At that stage, many of the mud-plaster walls had crumbled. The maximum recorded base shear coefficient was 0.5.