• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.93-100
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• 2001

The three dimensional(3D) reconstruction from two dimensional(2D) image data is using in many fields such as RPD(Rapid Product Development) and reverse engineering. In this paper, the main step of 3D reconstruction is comprised of two steps : image processing step and B-spline surface approximation step. In the image processing step, feature points of each cross-section are obtained by means of several image processing technologies. In the B-spline surface approximation step, using the data of feature points obtained in the image processing step, the control points of B-spline surface are obtained, which are used for IGES file of 3D CAD model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.155-157
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• 2012

In this paper, we propose a nonlinear 3D image correlator using computational reconstruction of 3D images based on integral imaging. In the proposed method, the elemental images for reference 3D object and target 3D object are recorded through the lens array. The recorded elemental images are reconstructed as reference plane image and target plane images using the computational integral imaging reconstruction algorithm and the nonolinear correlation between them is performed for object recognition. To show the usefulness of the proposed method, the preliminary experiments are carried out and the experimental results are presented compared with the conventional results.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.251-252
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• 2009

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.74-82
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• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• ETRI Journal
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• v.25 no.5
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• pp.345-355
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• 2003

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.60-66
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• 2019

In this paper, we propose a new free-view three-dimensional (3D) computational reconstruction of integral imaging to improve the visual quality of reconstructed 3D images when low-resolution elemental images are used. In a conventional free-view reconstruction, the visual quality of the reconstructed 3D images is insufficient to provide 3D information to applications because of the shift and sum process. In addition, its processing speed is slow. To solve these problems, our proposed method uses a pixel rearrangement technique (PERT) with locally selective elemental images. In general, PERT can reconstruct 3D images with a high visual quality at a fast processing speed. However, PERT cannot provide a free-view reconstruction. Therefore, using our proposed method, free-view reconstructed 3D images with high visual qualities can be generated when low-resolution elemental images are used. To show the feasibility of our proposed method, we applied it to optical experiments.

• Current Optics and Photonics
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• v.8 no.3
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• pp.246-258
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• 2024

In aerospace and energy engineering, the reconstruction of three-dimensional (3D) temperature distributions is crucial. Traditional methods like algebraic iterative reconstruction and filtered back-projection depend on voxel division for resolution. Our algorithm, blending deep learning with computer graphics rendering, converts 2D projections into light rays for uniform sampling, using a fully connected neural network to depict the 3D temperature field. Although effective in capturing internal details, it demands multiple cameras for varied angle projections, increasing cost and computational needs. We assess the impact of camera number on reconstruction accuracy and efficiency, conducting butane-flame simulations with different camera setups (6 to 18 cameras). The results show improved accuracy with more cameras, with 12 cameras achieving optimal computational efficiency (1.263) and low error rates. Verification experiments with 9, 12, and 15 cameras, using thermocouples, confirm that the 12-camera setup as the best, balancing efficiency and accuracy. This offers a feasible, cost-effective solution for real-world applications like engine testing and environmental monitoring, improving accuracy and resource management in temperature measurement.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.196-203
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• 2016

In this paper, we propose a virtual surgical planning system specialized to mandible reconstruction surgery. Mandible reconstruction surgery is one of the most difficult surgeries, even for experienced surgeons. Compared to the traditional surgical procedures, virtual surgical planning can reduce the operation time in operating room while expecting better surgical outcome with optimized planning. However, with existing software systems, it requires much time and manual operations in virtual surgical planning. To reduce preparation time and improve accuracy of virtual surgical planning, we have developed optimized functions for virtual surgical simulation of mandible reconstruction with user-friendly interface. We found that the proposed system shortened the preparation time by half compared to the existing system from the experiments. The proposed system supports surgeons to make accurate plan faster and easier. The virtually planned results are used to make surgical cutting guide by 3D printing, and this will enhance surgical performance in operating room.

• ETRI Journal
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• v.37 no.1
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• pp.138-146
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• 2015

This paper presents a new non-constraining online optical handwritten signature reconstruction system that, in the main, makes use of a transparent glass pad placed in front of a color camera. The reconstruction approach allows efficient exploitation of hand activity during a signing process; thus, the system as a whole can be seen as a viable alternative to other similar acquisition tools. This proposed system allows people with physical or emotional problems to carry out their own signatures without having to use a pen or sophisticated acquisition system. Moreover, the developed reconstruction signature algorithms have low computational complexity and are therefore well suited for a hardware implementation on a dedicated smart system.