In this study, we focus on the behavior of oil floating on the water, oil bubble, for a flexible display surface and propose Oil Bubble Display that allows interaction with an image corresponding to the shape of flexible display surface. The system enables users to deform, fuse and separate the oil bubble and to interact with projected images. In order to project images onto oil bubbles, we mixed powder materials with the oil which scatter the projected light. In this paper, we implemented shape deformation of projected images, mixing and decomposition of projected colors, and summation and distribution of projected numbers. We then investigated the contrast and the time variation of flexibility. As a result, the concentration of powder materials for high contrast was found and appropriate flexibility was kept up to 15 times of operation.

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Earthenware fragments are manually assembled. However, there is risk that the earthenware fragments are damaged during the manual work. According to this situation, a system which can help a user to assemble the fragments with the visual information in a computer is developed. Our system are combined with the interface which is used by placing the fragments and matching function in 3D. The data of the earthenware fragments used in this paper is measured by the 3D measurement device. In our method, the measured point clouds are displayed in 2D plane at first. Then, the user can match the fragments with the features of patterns and rim parts. Based on a fixed order which can help the user to assemble the fragments, the earthenware fragments are assembled. Experiments have shown that our method works well and is of great benefit to assembling the earthenware fragments.

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A user controlled texture synthesis technique reproduces the characteristic color pattern of a sample image on an output image in accordance with a paint image given by a user. This technique does not specially treat the contour of an object, that is, the boundary between an object and its background on the sample image. Thus, when a user wants to use only the pixels of the object for no background or other backgrounds in the synthesis, it is difficult to reproduce the characteristic contour of the object on an output image in accordance with the contour of a paint region roughly painted by the user. Therefore, a boundary expansion texture synthesis technique was proposed to reproduce the characteristic object contour of a sample image by appropriately expanding the contour of a paint region based on the user controlled texture synthesis. In this paper, we propose a transparent boundary expansion texture synthesis technique based on the previous technique. Our new technique reproduces the finer object contour as well as the characteristic color pattern of a sample image by using opacity values, alphas, given to pixels of sample and paint images.

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In this research, we propose an image montage method to synthesize a natural-looking output image by automatically determining the optimal relative arrangement of two input images of different scenes to montage. In this method, the two input images are relatively arranged so as to overlap each other partially. The overlapping region is searched for the most similar paths in both of vertical and horizontal directions, each of which is the chain of pixels with the most similar color distribution between the two input images. An efficient multiresolution method determines the optimal relative arrangement that has the most similar paths with the highest similarity among all relative arrangements. The most similar path is found by the patch-based image quilting search method, which we have developed based on the pixel-based search method used in the image quilting texture synthesis. This patch-based search method evaluates the similarity between two patches overlapping each other, which come from the two input images respectively. The method finds the most similar path that has the chain of patches with the highest similarity along the path. The similarity between two patches is evaluated using their color histograms. After determining the optimal relative arrangement, the "boundary region" and "copy regions" are determined using the most similar paths of both directions. The two input images are stitched together along the boundary region. The copy region copied from each input image is pasted on the output image as it is. The output image is completed by applying feathering and texture synthesis, or Poisson image editing to the boundary region. A "preserved region" can be assigned in each input image in order to include the region on the output image.

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