• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.81-93
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• 1993

The three dimensional(3D) shape reconstruction from two dimensional(2D) cross-sections can be completed through three main phases : the input compilation, the triangular grid formation, and the smooth surface construction. In the input compilation phase, the cross-sections are analyzed to exctract the input data required for the shape reconstruction. This data includes the number of polygonized contours per cross-section and the vertices defining each polygonized contour. In the triangular grid formation phase, a triangular grid, leading to a polyhedral approximations, is constructed by extracting all the information concerning contour links between two adjacent cross- sections and then performing the appropriate triangulation procedure for each contour link. In the smooth surface construction phase, a smooth composite surface interpolating all vertices on the triangular grid is constructed. Both the smooth surface and the polyhedral approximation can be used as reconstructed models of the object. This paper proposes a new method for reconstructing the geometric model of a 3D objdect from a sequence of planar contours representing 2D cross-sections of the objdect. The method includes the triangular grid formation algorithms for contour closing, one-to-one branching, and one-to-many braanching, and many-to-many branching. The shape reconstruction method has been implemented on a SUN workstation in C.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.500-506
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• 2014

A new 3-D reconstruction algorithm for the human face is proposed using the derivative Moir$\acute{e}$ topography which ensures fast and robust reconstruction even for rough surfaces. The Moir$\acute{e}$ interference fringe pattern is initially obtained through the projection Moir$\acute{e}$ topography based on phase shifting, and then differentiated to provide a full unwrapped phase map for a human face. $2{\pi}$ ambiguity, which has been a chronically unsolved problem with Moir$\acute{e}$ topography, is successfully surmounted by differentiating the Moir$\acute{e}$ fringe patterns both in x- and y-directions when the object is located in the x-y plane. A real human face is used for verifying the proposed derivative Moir$\acute{e}$ topography. A human face of 4 different phase-shifted images taken in the fixed plane is almost fully reconstructed in 3-D format in 0.1 mm lateral resolution.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.9-17
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• 2007

Feature based stereo matching is an effective way to perform 3D building reconstruction. However, in urban scene, the cluttered background and various building structures may interfere with the performance of building reconstruction. In this paper, we propose a novel method to robustly reconstruct buildings on the basis of rectangle regions. Firstly, we propose a multi-scale linear feature detector to obtain the salient line segments on the object contours. Secondly, candidate rectangle regions are extracted from the salient line segments based on their local information. Thirdly, stereo matching is performed with the list of matching line segments, which are boundary edges of the corresponding rectangles from the left and right image. Experimental results demonstrate that the proposed method can achieve better accuracy on the reconstructed result than pixel-level stereo matching.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1658-1667
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• 2008

Reconstruction of 3D objects from a single view image is generally an ill-posed problem because of the projection distortion. A monocular vision based 3D object localization method is proposed in this paper, which approximates an object on the ground to a simple bounding solid and works automatically without any prior information about the object. A spherical or cylindrical object determined based on a circularity measure is approximated to a bounding cylinder, while the other general free-shaped objects to a bounding box or a bounding cylinder appropriately. For a general object, its silhouette on the ground is first computed by back-projecting its projected image in image plane onto the ground plane and then a base rectangle on the ground is determined by using the intuition that touched parts of the object on the ground should appear at lower part of the silhouette. The base rectangle is adjusted and extended until a derived bounding box from it can enclose the general object sufficiently. Height of the bounding box is also determined enough to enclose the general object. When the general object looks like a round-shaped object, a bounding cylinder that encloses the bounding box minimally is selected instead of the bounding box. A bounding solid can be utilized to localize a 3D object on the ground and to roughly estimate its volume. Usefulness of our approach is presented with experimental results on real image objects and limitations of our approach are discussed.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.65-74
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• 2021

3D reconstruction means that reconstructing the 3D shape of the object in an image and a video. We proposed a progressive occupancy network architecture that can recover not only the overall shape of the object but also the local details. Unlike the original occupancy network, which uses a feature vector embedding information of the whole image, we extract and utilize the different levels of image features depending on the receptive field size. We also propose a novel network architecture that applies the image features sequentially to the decoder blocks in the decoder and improves the quality of the reconstructed 3D shape progressively. In addition, we design a novel decoder block structure that combines the different levels of image features properly and uses them for updating the input point feature. We trained our progressive occupancy network with ShapeNet. We compare its representation power with two prior methods, including prior occupancy network(ONet) and the recent work(DISN) that used different levels of image features like ours. From the perspective of evaluation metrics, our network shows better performance than ONet for all the metrics, and it achieved a little better or a compatible score with DISN. For visualization results, we found that our method successfully reconstructs the local details that ONet misses. Also, compare with DISN that fails to reconstruct the thin parts or occluded parts of the object, our progressive occupancy network successfully catches the parts. These results validate the usefulness of the proposed network architecture.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.2
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• pp.151-159
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• 2002

The method of accumulating a sequence of focused images is usually used for reconstruction of 3D object\\`s shape. To acquire a focused image, the conventional methods must calculate the focus measures of all pixels resulting in a long measurement time. This paper proposes a new method of reducing the computation time spent for deciding the focused pixels in the input image, which predicts the area in the image to calculate the focus measure based on a priori information on the object to be measured. The proposed algorithm estimates the area to consider in the next measurement based on the focused area in the present measurement. As the focus measure, Laplacian measure was used in this paper and the experiments have shown that the preposed algorithm may significantly reduce the calculation time. Although, as implied, this algorithm can be applied to only simple objects at this stage, advanced representation schemes will eliminate the restrictions on application domain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.199-210
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• 1998

In this paper, we present a 3D reconstruction method of color volume data for a computerized human atlas. Binary volume rendering which takes the advantages of object-order ray traversal and run-length encoding visualizes 3D organs at an interactive speed in a general PC without the help of specific hardwares. This rendering method improves the rendering speed by simplifying the determination of the pixel value of an intermediate depth image and applying newly developed normal vector calculation method. Moreover, we describe the 3D boundary encoding that reduces the involved data considerably without the penalty of image quality. The interactive speed of the binary rendering and the storage efficiency of 3D boundary encoding will accelerate the development of the PC-based human atlas.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.90-97
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• 2023

Digital holographic microscopy (DHM) is a three-dimensional (3D) imaging technique that uses the phase information of coherent light. In the reconstruction process of DHM, a narrow region around the positive or negative sideband from the Fourier domain is windowed to avoid noise due to the DC spectrum of the hologram spectrum. However, the limited size of the window also degrades the high-frequency information of the 3D object profile. Although a large window can have more detailed information of the 3D object shape, the noise is increased. To solve this trade-off, we propose phase difference averaging (PDA). The proposed method yields high-frequency information of the specimen while reducing the DC noise. In this paper, we explain the reconstruction algorithm for this method and compare it to various conventional filtering methods including Gaussian, Wiener, average, median, and bilateral filtering methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.92-99
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• 1997

Nowadays, Electronic Speckle Pattern Interferometry is a well-established measuring technique with a wide range of industrial applications, particularly in the fields of deformation measurement and vibration analysis. Comparing with holographic interferometry, it has some attractive features, which are rapid recording and reconstruction, satisfiable automation etc. The Time-Average ESPI is used to provide vibration mode shape of an object whose vibration amplitude is given as a fringe pattern. Its merit is rapid and simple measurement for vibrating object. However, it is not possible to determine the direction of motions of a point on the object at any given time, because it does not give any information about the phase of vibration. But, Stroboscopic ESPI can measure the amplitude and phase of vibrating surface. In this paper, loudspeakers were tested by these two methods. As a result, we can assume that these techniques will be applied directly in the loudspeaker industry.