• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1393-1395
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• 2003

In this research, we presented a data integration, which integrates ultra high resolution images and complementary data for 3D building reconstruction. In our method, as the ultra high resolution image, Three Line Sensor (TLS) images are used in combination with 2D digital maps, DSMs and both of them. Reconstructed 3D buildings, correctness rate and the accuracy of results were presented. As a result, optimized combination scheme of data sets , sensors and methods was proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1853-1859
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• 2008

In this paper, we propose a novel method to improve the visual quality of reconstructed images for 3D pattern recognition based on the computational integral imaging reconstruction (CIIR). The proposed CIIR method provides improved 3D reconstructed images by superimposing magnified elemental images by a combination of a round mapping model and image interpolation algorithms. To objectively evaluate the proposed method, we introduce an experimental framework for a computational pickup process and a CIIR process using a Gaussian function and evaluate the proposed method. We also carry out experiments on 3D objects and present their results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2045-2053
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• 2016

Many research institutes have studied 3D stereoscopic images since the release of 3D stereoscopic film 'Avatar' in 2009. Universities have conducted research on and studied 3D stereoscopic image in various ways, and even university curriculums have adopted 3D stereoscopic image production courses. However, universities face many difficulties in purchasing expensive equipment including cameras and rigs for 3D stereoscopic image contents production training. This paper addresses the 3D stereoscopic image content production curriculum using software in university. A practical training course was carried out based on the theoretical contents and theories that must be dealt with in 3D stereoscopic image contents production curriculum. As a result, students could understand the principles of 3D stereoscopic image production and produce various 3D stereoscopic images using various software applications. In this parer, proper instructional methods for 3D stereoscopic image contents production in university are discussed through this production course.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.390-392
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• 2003

Video mosaicing techniques have been widely used in virtual reality environments. Especially in GIS field, video mosaics are becoming more and more common in representing urban environments. Such applications mainly use spherical or panoramic mosaics that are based on images taken from a rotating camera around its nodal point. The viewpoint, however, is limited to location within a small area. On the other hand, 2D-mosaics, which are based on images taken from a translating camera, can acquire data in wide area. The 2D-mosaics still have some problems : it can‘t be applied to images taken from a rotational camera in large angle. To compensate those problems , we proposed a novel method for creating video mosaics in 3D space. The proposed algorithm consists of 4 steps: feature -based optical flow detection, camera orientation, 2D-image projection, and image registration in 3D space. All of the processes are fully automatic and successfully implemented and tested with real images.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.257-262
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• 2016

This study aimed to suggest a novel method of modeling a hearing aid ear shell based on Digital Imaging and Communication in Medicine (DICOM) in the hearing aid ear shell manufacturing method using a 3D printer. In the experiment, a 3D external auditory meatus was extracted by using the critical values in the DICOM volume images, and the modeling surface structures were compared in standard type STL (STereoLithography) files which could be recognized by a 3D printer. In this 3D modeling method, a conventional ear model was prepared, and the gaps between adjacent isograms produced by a 3D scanner were filled with 3D surface fragments to express the modeling structure. In this study, the same type of triangular surface structures were prepared by using the DICOM images. The result showed that the modeling surface structure based on the DICOM images provide the same environment that the conventional 3D printers may recognize, eventually enabling to print out the hearing aid ear shell shape.

• Imaging Science in Dentistry
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• v.42 no.1
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• pp.25-33
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• 2012

Purpose : This study was performed to determine the accuracy of linear measurements on three-dimensional (3D) images using multi-detector computed tomography (MDCT) and cone-beam computed tomography (CBCT). Materials and Methods : MDCT and CBCT were performed using 24 dry skulls. Twenty-one measurements were taken on the dry skulls using digital caliper. Both types of CT data were imported into OnDemand software and identification of landmarks on the 3D surface rendering images and calculation of linear measurements were performed. Reproducibility of the measurements was assessed using repeated measures ANOVA and ICC, and the measurements were statistically compared using a Student t-test. Results : All assessments under the direct measurement and image-based measurements on the 3D CT surface rendering images using MDCT and CBCT showed no statistically difference under the ICC examination. The measurements showed no differences between the direct measurements of dry skull and the image-based measurements on the 3D CT surface rendering images (P>.05). Conclusion : Three-dimensional reconstructed surface rendering images using MDCT and CBCT would be appropriate for 3D measurements.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.717-725
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• 2015

Prostate images have been used in the diagnosis of prostate using TRUS images being relatively cheap. Ultrasound images are recorded with 3 dimension and one diagnostic exam is made with a number of the images. A doctor can see 2 dimensional images on the monitor sequentially and 3 dimensional ones to diagnose a disease. To display the images, 2-d images are used with raw 2-d ones, but 3-d images need to be segmented by the prostates and their backgrounds to be seen from different angles and with cut images of inner side. Especially on detecting the boundary, the ones in the middle of all images are easy to find the boundary but the base and apex of the images are hard to do it since there are lots of uncertain boundary. So, in this paper we propose the method that applies an average shape model and detects the boundary, and shows its superiority compared to the existing methods with experiments.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1404-1407
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• 2002

Although we look at objects as 2D images through our eyes, we can reconstruct the shape and/or depth of objects. In order to realize this ability using computers, it is required that the method which can estimate the 3D features of object from 2D images. As feature which represents 3D shapes effectively, three dimensional vector autoregressive model is pro- posed. If this feature is associated other feature of 2D shape, then above aim might be achieved. On the other hand, as feature which represents 2D shapes, quasi moment features is proposed. As the first step of association of these features, we constructed real time simulator that computes both of two features concurrently from object data (3D curves) . This simulator can also rotate object and estimate the rotation The method using 3D VAR model estimates the rotation correctly, but the estimation by quasi moment features includes much errors. This reason would be that projected images are constructed by the points only, and doesn't have enough sizes to estimate the correct 3D rotation parameters.

• The Korean Journal of Nuclear Medicine
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• v.33 no.3
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• pp.327-336
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• 1999

Purpose: To assess the quantitative accuracy and the clinical utility of 3D volumetric PET imaging with FDG in brain studies, 24 patients with various neurological disorders were studied. Materials and Methods: Each patient was injected with 370 MBq of 2-[$^{18}F$]fluoro-2-deoxy-D-glucose. After a 30 min uptake period, the patients were imaged for 30 min in 2 dimensional acquisition (2D) and subsequently for 10 min in 3 dimensional acquisition imaging (3D) using a GE $Advance^{TM}$ PET system, The scatter corrected 3D (3D SC) and non scatter-corrected 3D images were compared with 2D images by applying ROIs on gray and white matter, lesion and contralateral normal areas. Measured and calculated attenuation correction methods for emission images were compared to get the maximum advantage of high sensitivity of 3D acquisition. Results: When normalized to the contrast of 2D images, the contrasts of gray to white matter were $0.75{\pm}0.13$ (3D) and $0.95{\pm}0.12$ (3D SC). The contrasts of normal area to lesion were $0.83{\pm}0.05$ (3D) and $0.96{\pm}0.05$ (3D SC). Three nuclear medicine physicians judged 3D SC images to be superior to the 2D with regards to resolution and noise. Regional counts of calculated attenuation correction was not significantly different to that of measured attenuation correction. Conclusion: 3D PET images with the scatter correction in FDG brain studies provide quantitatively and qualitatively similar images to 2D and can be utilized in a routine clinical setting to reduce scanning time and patient motion artifacts.

• Journal of Sensor Science and Technology
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• v.23 no.6
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• pp.377-382
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• 2014

Detecting and segmenting diffuse targets in laser ranging data is a critical problem for tactical reconnaissance. In this study, we propose a new method that facilitates the characterization of diffuse irregularly shaped objects using "spin images," i.e., local 2D histograms of laser returns oriented in 3D space, and a clustering process. The proposed "cluster-based spin imaging" method resolves the problem of using standard spin images for diffuse targets and it eliminates much of the computational complexity that characterizes the production of conventional spin images. The direct processing of pre-segmented laser points, including internal points that penetrate through a diffuse object's topmost surfaces, avoids some of the requirements of the approach used at present for spin image generation, while it also greatly reduces the high computational time overheads incurred by searches to find correlated images. We employed 3D airborne range data over forested terrain to demonstrate the effectiveness of this method in discriminating the different geometric structures of individual tree clusters. Our experiments showed that cluster-based spin images have the potential to separate classes in terms of different ages and portions of tree crowns.