• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.906-915
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• 2006

This study concerns an advanced 3D surface reconstruction method that the vertices of surface model can be completely matched to the unstructured point cloud measured from arbitrary complex shapes. The concept of bounding voxel model is introduced to generate the mesh model well-representing the geometrical and topological characteristics of point cloud. In the reconstruction processes, the application of various methodologies such as shrink-wrapping, mesh simplification, local subdivision surface fitting, insertion of is isolated points, mesh optimization and so on, are required. Especially, the effectiveness, rapidity and reliability of the proposed surface reconstruction method are demonstrated by the simulation results for the geometrically and topologically complex shapes like dragon and human mouth.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.11-18
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• 2013

This paper presents a SFF(shape from focus) algorithm using a new focus measure based on higher order statistics for the exact depth estimation. Since conventional SFF-based 3D depth reconstruction algorithms used SML(sum of modified Laplacian) as the focus measure, their performance is strongly depended on the image characteristics. These are efficient only for the rich texture and well focused images. Therefore, this paper adopts a new focus measure using HOS(higher order statistics), in order to extract the focus value for relatively poor texture and focused images. The initial best focus area map is generated by the measure. Thereafter, the area refinement, thinning, and corner detection methods are successively applied for the extraction of the locally best focus points. Finally, a 3D model from the carefully selected points is reconstructed by Delaunay triangulation.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1515-1526
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• 2022

Image-based 3D reconstruction is to restore the shape and color of real-world objects, and image sensors mounted on mobile platforms are used for positioning and mapping purposes in indoor and outdoor environments. Due to the increase in accidents in underground space, the location accuracy problem of underground spatial information has been raised. Image-based location estimation studies have been conducted with the advantage of being able to determine the 3D location and simultaneously identify internal damage from image data acquired from the inside of pipeline-type underground facilities. In this study, we studied 3D reconstruction based on the images acquired inside the pipe-type underground facility and reference data. An unmanned mobile system equipped with a stereo camera was used to acquire data and image data within a pipe-type underground facility where reference data were placed at the entrance and exit. Using the acquired image and reference data, the pipe-type underground facility is reconstructed to a geo-referenced 3D shape. The accuracy of the 3D reconstruction result was verified by location and length. It was confirmed that the location was determined with an accuracy of 20 to 60 cm and the length was estimated with an accuracy of about 20 cm. Using the image-based 3D reconstruction method, the position and line-shape of the pipe-type underground facility will be effectively updated.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2375-2378
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• 2003

In manufacture of printed circuit boards, one important issue is precisely to measure the three-dimensional shape of the solder paste silk-screened prior to direct surface mounting of chips. This paper presents the 3D shape reconstruction of solder paste using the optical triangulation method based on structured light or slit beam and the measurement algorithm for height, volume. area, and coplanarity on component pads from the 3D range image. Futhermore, statistical process control function is incorporated for process capability analysis.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.363-369
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• 2008

In this paper, we have proposed 3D shape reconstruction using superquadrics and single z-buffer Constructive Solid Geometry (CSG) rendering algorithm. Superquadrics can obtain various 3D model using 11 parameters and both superquadrics and deformed-superquadrics play a role of primitives which are consisted of CSG tree. In addition, we defined some effective equations using z-buffer algorithm and stencil buffer for synthesizing 3D model. Using this proposed algorithm, we need not to consider the coordinate of each 3D model because we simply compare the depth value of 3D model.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.244-247
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• 1995

A technique is presented for evaluating spinal deformity of a human back by extracting a spinal line based on 3-D topograpic reconstruction of the back from its moire image. A given moire image is differentiatedby DOG filter to extract moire stripes. The stripes are then assigned labels and the labels are interpolated by the Lagrange polynomial to yield the undulation of the back which gives a relative 3-D shape of the back. A valley is searched on the undulation near the middle part of the back and the valley line is finally extracted as an approximated spinal line. The mean differenceand the variance between the spinal line and the middle line are calculated and reported. Experiment is performed employing real moire images ofjunior-high school students' backs and some of the results are shown with discussion.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.57-61
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• 2014

We present a robust 3D facial reconstruction method using a single image generated by face-specific super resolution technique. Based on the several consecutive frames with low resolution, we generate a single high resolution image and a three dimensional facial model based on it. To do this, we apply PME method to compute patch similarities for SR after two-phase warping according to facial attributes. Based on the SRI, we extract facial features automatically and reconstruct 3D facial model with basis which selected adaptively according to facial statistical data less than a few seconds. Thereby, we can provide the facial image of various points of view which cannot be given by a single point of view of a camera.

• Journal of the Semiconductor & Display Technology
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• v.12 no.2
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• pp.27-32
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• 2013

Shape From Focus (SFF) is a passive optical technique to recover 3D structure of an object that utilizes focus information from 2D images of the object taken at different focus levels. Mostly, SFF methods use a single focus measure to compute image focus quality of each pixel in the image sequence. However, it is difficult to recover accurate 3D shape using a single focus measure, as different focus measures perform differently in diverse conditions. In this paper, a nonlinear Total Variation (TV) based approach is proposed for 3D shape recovery. To improve the result of surface reconstruction, several initial depth maps are obtained using different focus measures and the resultant 3D shape is obtained by diffusing them through TV. The proposed method is tested and evaluated by using image sequences of synthetic and real objects. The results and comparative analysis demonstrate the effectiveness of our method.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.