• KIPS Transactions on Computer and Communication Systems
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• v.4 no.8
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• pp.245-252
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• 2015

Recently, parallel processing methods with accelerator have been introduced into a high performance computing and a mobile computing. The photomosaic application can be parallelized by using inherent data parallelism and accelerator. In this paper, we propose a way to distribute the workload of the photomosaic application into a CPU and GPU heterogeneous computing environment. That is, the photomosaic application is parallelized using both CPU and GPU resource with the asynchronous mode of OpenCL, and then the optimal workload distribution rate is estimated by measuring the execution time with CPU-only and GPU-only distribution rates. The proposed approach is simple but very effective, and can be applied to parallelize other applications on a CPU and GPU heterogeneous computing environment. Based on the experimental results, we confirm that the performance is improved by 141% into a heterogeneous computing environment with the optimal workload distribution compared with using GPU-only method.

• Journal of the Korea Computer Graphics Society
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• v.14 no.1
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• pp.17-25
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• 2008

We proposed the method for photomosaic generation using a programmable GPU. We design vertices to generate a photomosaic through a graphics pipeline and suggest a texture representation of an image database whice is used for tile. Both the source image and the tiles are stored to texture, which are matched by a vertex shader and drawn by a fragment shader. This is much faster than several techniques which achieve the best match for each tile.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.1-8
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• 2012

Mosaic is to make a big image by gathering lots of small materials having various colors. With advance of digital imaging techniques, photomosaic techniques using photos are widely used. In this paper, we presents an automatic photomosaic algorithm based on adaptive tiling and block matching. The proposed algorithm is composed of two processes: photo database generation and photomosaic generation. Photo database is a set of photos (or tiles) used for mosaic, where a tile is divided into $4{\times}4$ regions and the average RGB value of each region is the feature of the tile. Photomosaic generation is composed of 4 steps: feature extraction, adaptive tiling, block matching, and intensity adjustment. In feature extraction, the feature of each block is calculated after the image is splitted into the preset size of blocks. In adaptive tiling, the blocks having similar similarities are merged. Then, the blocks are compared with tiles in photo database by comparing euclidean distance as a similarity measure in block matching. Finally, in intensity adjustment, the intensity of the matched tile is replaced as that of the block to increase the similarity between the tile and the block. Also, a tile redundancy minimization scheme of adjacent blocks is applied to enhance the quality of mosaic photos. In comparison with Andrea mosaic software, the proposed algorithm outperforms in quantitative and qualitative analysis.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.139-146
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• 2011

We propose a photomosaic method using PCA(Principal Component Analysis), which uses PCA results to find the most similar candidate fast and correctly. When two images are projected onto a certain principal component, if their coefficients are similar, they are also likely to be similar. Thus our photomosaic method using PCA can take care of both colors and shapes of images. Our method using coefficient comparison is faster than the one using all color comparison and more correct than the one using average comparison. Our hardware accelerated photomosaic algorithm can handle video images in real-time.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.502-507
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• 2009

We present a real-time photomosaics method for small image set optimized by feature selection method. Photomosaics is an image that is divided into cells (usually rectangular grids), each of which is replaced with another image of appropriate color, shape and texture pattern. This method needs large set of tile images which have various types of image pattern. But large amount of photo images requires high cost for pattern searching and large space for saving the images. These requirements can cause problems in the application to a real-time domain or mobile devices with limited resources. Our approach is a genetic feature selection method for building an optimized image set to accelerate pattern searching speed and minimize the memory cost.

• Journal of the Korea Computer Graphics Society
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• v.17 no.1
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• pp.25-31
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• 2011

Photomosaic is a method of representation an input image in forms of mosaics by a set of small tile images. Generally, equal rectangular tiles are used in photo mosaics. Therefore, there are limitations to expression of mosaic according to characteristic of images. In this paper, photo mosaics using quad-tree structure is proposed to create tiles in varies sizes. Initially, color variance per each level of an input image is computed using the mipmap of graphic hardware. Depending on the value of Valiance, the input image is divided into tiles in varies sizes. Each tile finds the most similar reference image and replaces with it. As a result, the method provides another pictorial effectiveness by dividing the input image into tiles in varies sizes depending on color held by the input image. In addition, whole processing is done on the graphic hardware and thereby we achieve faster performance.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1282-1295
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• 2006

This paper proposes a method of image tile mosaics to preserve detailed depiction of the source image. This method enhance the shortcoming of the previous mosaic methods that cannot express the detailed depiction because of the gap between tiles. Our method is implemented by the usage of image tiles to preserve detailed depiction of the source image, as well as the usage of 2-layered tiles to.eliminate the gap between tiles. The method suggested in this paper are composed of following process. First of all, the position of the upper layer tile is located through a centroidal voronoi diagram to which an edge avoidance technique is applied, and the position of the lower layer tile is calculated using Delaunay triangulation. Secondly, discover the size and direction field of the tile considering the relation between tiles. Thirdly, adopt a photomosaic technique to use the image tiles. At this time, the technique of multi-level indexing is used to accelerate the speed of image searching. Through above process, the gap between tiles is minimized against other methods and a mosaic image with a maximized detailed description is achieved.