• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.633-641
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• 2015

In this study, we proposed a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, a camera, and a turntable. For laser-camera calibration a new and simple method was proposed. 3D point cloud data of the surface of scanned object was fully collected by integrating extracted laser profiles, which were extracted from laser stripe images, corresponding to rotary angles of the rotary mechanism. The obscured laser profile problem was also solved by adding an addition camera at another viewpoint. From collected 3D point cloud data, the 3D model of the scanned object was reconstructed based on facet-representation. The reconstructed 3D models showed effectiveness and the applicability of the proposed 3D scanning system to 3D model-based applications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1634-1637
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• 2003

Any given object on the motor-driven turntable is pictured from 8 to 72 different views with a digital camera. 3D shape reconstruction is performed with the integrated software called by Scanware from these multiple digital photographs. There are several steps such as configuration, calibration, capturing, segmentation, shape creation, texturing and merging process during the shape reconstruction process. 3D geometry data can be exported to cad data such as Autocad input file. Also 3D image model is generated from 3D geometry and texture data, and is used to advertise the model in the internet environment. Consumers can see the object realistically from wanted views by rotating or zooming in the internet browsers with Scanbull spx plug-in. The spx format allows a compact saving of 3D objects to handle or download. There are many types of scan equipments such as laser scanners and photogrammetric scanners. Line or point scan methods by laser can generate precise 3D geometry but cannot obtain color textures in general. Reversely, 3D image modeling with photogrammetry can generate not only geometries but also textures from associated polygons. We got various 3D image models and introduced the process of getting 3D image model of an internet-connected watchdog robot.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.116-122
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• 2016

This paper proposes a practical object shape reconstruction method using an underwater imaging sonar. In order to reconstruct the object shape, three methods are utilized. Firstly, the vertical field of view of imaging sonar is modified to narrow angle to reduce an uncertainty of estimated 3D position. The wide vertical field of view makes the incorrect estimation result about the 3D position of the underwater object. Secondly, simple noise filtering and range detection methods are designed to extract a distance from the sonar image. Lastly, a low pass filter is adopted to estimate a probability of voxel occupancy. To demonstrate the proposed methods, object shape reconstruction for three sample objects was performed in a basin and results are explained.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.70-78
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• 2021

Estimating 3D information from a single image is one of the essential problems in numerous applications. Since a 2D image inherently might originate from an infinite number of different 3D scenes, thus 3D reconstruction from a single image is notoriously challenging. This challenge has been overcame by the advent of recent deep convolutional neural networks (CNNs), by modeling the mapping function between 2D image and 3D information. However, to train such deep CNNs, a massive training data is demanded, but such data is difficult to achieve or even impossible to build. Recent trends thus aim to present deep learning techniques that can be trained in a weakly-supervised manner, with a meta-data without relying on the ground-truth depth data. In this article, we introduce recent developments of weakly-supervised deep learning technique, especially categorized as scene 3D reconstruction and object 3D reconstruction, and discuss limitations and further directions.

• Current Optics and Photonics
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• v.6 no.6
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• pp.598-607
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• 2022

In this paper, a simple nondestructive technology is used to investigate unstained biological blood cells in three dimensions (3D). The technology employs a reflective phase-only spatial light modulator (SLM) for displaying the phase hologram of the object being tested, and a Fourier lens for its reconstruction. The phase hologram is generated via superposing a digital random phase on the 2D image of the object. The phase hologram is then displayed by the SLM with 256 grayscale levels, and reconstructed by a Fourier lens to present the object in 3D. Since noise is the main problem in this method, the windowed Fourier filtering (WFF) method is applied to suppress the noise of the reconstructed object. The quality of the reconstructed object is refined and the noise level suppressed by approximately 40%. The technique is applied to objects: the National Institute of Standards (NIS) logo, and a film of unstained peripheral blood. Experimental results show that the proposed technique can be used for rapid investigation of unstained biological blood cells in 3D for disease diagnosis. Moreover, it can be used for viewing unstained white blood cells, which is still challenging with an optical microscope, even at large magnification.

• ETRI Journal
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• v.40 no.6
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• pp.788-793
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• 2018

3D reconstruction of urban architecture, land, and roads is an important part of building a "digital city." Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.288-289
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• 2022

In this paper, we propose a method of obtaining high density geometric information using multi-view structured light. Reconstruction error due to the difference in resolution between the projector and the camera occurs when reconstruction a 3D shape from a structured light system to a single projector. This shows that the error in the point cloud in 3D is also the same when reconstruction the shape of the object. So we propose a high density method using multiple projectors to solve such a reconstruction error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.4152-4158
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• 2012

The Stereo X-ray inspection system is designed for effectively providing the additional information of objects than the conventional inspection system that offers only 2D cross-section of objects. We studied the geometric improvement of the stereo X-ray inspection system, the stereo matching algorithm of the single object using the edge and the volume reconstruction method for the inspected object. In this paper, we conduct a matching algorithm to find the correspondences between the images and reconstruct 3-D shapes of real objects using the stereo X-ray images. Also, we apply a new 3D reconstruction algorithm for the discrimination of two objects. For the separation of the overlapping objects, we calculate the vector of the object and divide inner and outer voxel of objects. And for the elimination of the overlapping area, we study the reconstruct 3D shapes using the threshold based Z-axis. The experimental results show that the proposed technique can enhance the accuracy of stereo matching and give more efficient visualization for overlap objects in the restricted environment.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.804-809
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• 2004

It is essential to calibrate a camera in order to recover 3-dimensional reconstruction from uncalibrated images. This paper proposes a new technique of the camera calibration using a homography between the planar patterns image taken by the camera, which is located at the three planar patterns image. Since the proposed method should be computed from the homography among the three planar patterns from a single image, it is implemented more easily and simply to recover 3D object than the conventional. Experimental results show the performances of the proposed method are the better than the conventional. We demonstrate the examples of 3D reconstruction using the proposed algorithm from image sequence.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1402-1409
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• 1989

The algorithm to reconstruct an original 3-D object from a curved object is proposed in this paper. The reconstruction is performed by transforming the recorded image perspectively which is obtained from projecting arbitrary pattern on a curved object. In this paper we make use of the sequence of points, the set of points as a projection pattern of a projected image. The experimental result reveals that this algorithm makes it possible to acquisite 3-D information as well as depth information over the whole 3-D range of the object by measuring the data while convolving the experimental object.