• Journal of the Optical Society of Korea
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• v.16 no.2
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• pp.115-120
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• 2012

In this paper, we present a method to automatically quantify the three-dimensional (3D) volume of red blood cells (RBCs) using off-axis digital holographic microscopy. The RBCs digital holograms are recorded via a CCD camera using an off-axis interferometry setup. The RBCs' phase image is reconstructed from the recorded off-axis digital hologram by a computational reconstruction algorithm. The watershed segmentation algorithm is applied to the reconstructed phase image to remove background parts and obtain clear targets in the phase image with many single RBCs. After segmenting the reconstructed RBCs' phase image, all single RBCs are extracted, and the 3D volume of each single RBC is then measured with the surface area and the phase values of the corresponding RBC. In order to demonstrate the feasibility of the proposed method to automatically calculate the 3D volume of RBC, two typical shapes of RBCs, i.e., stomatocyte/discocyte, are tested via experiments. Statistical distributions of 3D volume for each class of RBC are generated by using our algorithm. Statistical hypothesis testing is conducted to investigate the difference between the statistical distributions for the two typical shapes of RBCs. Our experimental results illustrate that our study opens the possibility of automated quantitative analysis of 3D volume in various types of RBCs.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.73-76
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• 2001

A segmentation is a prior processing for medical image analysis and 3D reconstruction. This Paper provides the method to segment 3D Visible Human color images. Firstly, the reference images that have a initial curve are segmented using Balloon and the results are propagated to the adjacent images. In the propagation processing, the result of the adjacent slice is modified by Edge-limited SRG Finally, the 3D Balloon improves the segmentation results of each 2D slice. the proposed method's performance was verified through the experiments to segment thigh muscles of Visible Human color images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2251-2259
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• 2009

We propose an algorithm and system which generates 3D stereo image by composition of 2D image from 4 multiple clusters which 1 cluster was composed of 4 multiple cameras based on network. Proposed Schemes have a network-based client-server architecture for load balancing of system caused to process a large amounts of data with real-time as well as multiple cluster environments. In addition, we make use of JPEG compression and RAM disk method for better performance. Our scheme first converts input images from 4 channel, 16 cameras to binary image. And then we generate 3D stereo images after applying edge detection algorithm such as Sobel algorithm and Prewiit algorithm used to get disparities from images of 16 multiple cameras. With respect of performance results, the proposed scheme takes about 0.05 sec. to transfer image from client to server as well as 0.84 to generate 3D stereo images after composing 2D images from 16 multiple cameras. We finally confirm that our scheme is efficient to generate 3D stereo images in multiple view and multiple clusters environments with real-time.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.245-250
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• 2011

Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

• Journal of Biomedical Engineering Research
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• v.32 no.1
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• pp.15-24
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• 2011

While Compton imaging is recognized as a valuable 3-D technique in nuclear medicine, reconstructing an image from Compton scattered data has been of a difficult problem due to its computational complexity. The most complex and time-consuming computation in Compton camera reconstruction is to perform the conical projection and backprojection operations. To alleviate the computational burden imposed by these operations, we investigate a rebinning method which can convert conical projections into parallel projections. The use of parallel projections allows to directly apply the existing deterministic reconstruction methods, which have been useful for conventional emission tomography, to Compton camera reconstruction. To convert conical projections into parallel projections, a cone surface is sampled with a number of lines. Each line is projected onto an imaginary plane that is mostly perpendicular to the line. The projection data rebinned in each imaginary plane can then be treated as the standard parallel projection data. To validate the rebinning method, we tested with the representative deterministic algorithms, such as the filtered backprojection method and the algebraic reconstruction technique. Our experimental results indicate that the rebinning method can be useful when the direct application of existing deterministic methods is needed for Compton camera reconstruction.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.60-65
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• 2012

This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.55-59
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• 1989

A true three-dimensional cone-beam reconstruction (TTCR) algorithm for the complete sphere geometry is derived, which is applicable to the direct volume image reconstruction from 2-D cone-beam projections. The algorithm is based on the modified filtered backprojection technique which uses a set of 2-D space-invariant filters and is derived from the previously developed parallel-beam true three-dimensional reconstruction(TTR) algorithm. The proposed algorithm proved to be superior in spatial resolution compared with the parallel-beam TTR algorithm.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.414-418
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• 2014

In this paper, we present a method to detect the position of a 3D object in scattering media by using the axially distributed sensing (ADS) method. Due to the scattering noise of the elemental images recorded by the ADS method, we apply a statistical image processing algorithm where the scattering elemental images are converted into scatter-reduced ones. With the scatter-reduced elemental images, we reconstruct the 3D images using the digital reconstruction algorithm based on ray back-projection. The reconstructed images are used for the position detection of a 3D object in the scattering medium. We perform the preliminary experiments and present experimental results.