• Journal of Biomedical Engineering Research
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• v.26 no.1
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• pp.55-63
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• 2005

A novel imaging system for High-resolution Ultrasonic Transmission Tomography (HUTT) and soft tissue differentiation methodology for the HUTT system are presented. The critical innovation of the HUTT system includes the use of sub-millimeter transducer elements for both transmitter and receiver arrays and multi-band analysis of the first-arrival pulse. The first-arrival pulse is detected and extracted from the received signal (i.e., snippet) at each azimuthal and angular location of a mechanical tomographic scanner in transmission mode. Each extracted snippet is processed to yield a multi-spectral vector of attenuation values at multiple frequency bands. These vectors form a 3-D sinogram representing a multi-spectral augmentation of the conventional 2-D sinogram. A filtered backprojection algorithm is used to reconstruct a stack of multi-spectral images for each 2-D tomographic slice that allow tissue characterization. A novel methodology for soft tissue differentiation using spectral target detection is presented. The representative 2-D and 3-D HUTT images formed at various frequency bands demonstrate the high-resolution capability of the system. It is shown that spherical objects with diameter down to 0.3㎜ can be detected. In addition, the results of soft tissue differentiation and characterization demonstrate the feasibility of quantitative soft tissue analysis for possible detection of lesions or cancerous tissue.

• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.796-803
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• 2008

In this paper, we present a depth scaling method for multiview images that could provide an 3D depth that a user prefers. Unlike previous works that change a camera configuration, the proposed method utilizes depth data in order to carry out the scaling of a depth range requested by users. From multivew images and their corresponding depth data, depth data is transformed into a disparity and the disparity is adjusted in order to control the perceived depth. In particular, our method can deal with multiview images captured by multiple cameras, and can be expanded from stereoscopic to multiview images. Based upon a DSCQS subjective evaluation test, our experimental results tested on an automultiscopic 3D display show that the perceived depth is appropriately scaled according to user's preferred depth.

• Journal of Korea Game Society
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• v.12 no.4
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• pp.13-22
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• 2012

The wide-spread use of the broadband Internet service makes the cloud computing-based gaming service possible. A game program is executed on a cloud node and its live image is fed into a remote user's display device via video streaming. The user's input is immediately transmitted and applied to the game. The minimization of the time to process remote user's input and transmit the live image back to the user and thus satisfying the requirement of instant responsiveness for gaming makes it possible. However, the cost to build its servers can be very expensive to provide high quality 3D games because a general purpose graphics system that cloud nodes are likely to have for the service supports a single 3D application at a time. Thus, the server must have a technology of 'realtime multiple rendering' to execute multiple 3D games simultaneously. This paper proposes a new architecture of 2-tier servers of clouds nodes of which one group executes multiple games and the other produces game's live images. It also performs a few experimentations to prove the feasibility of the new architecture.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1347-1355
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• 2015

In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition performance. Honda/UCSD database consists of 20 people, with 5 poses per person for a total of 500 face images. Extracted image consists of 5 poses using Multiple-Space PCA and each pose is performed by using (2D)²PCA for performing pose classification. Linear polynomial function is used as connection weight of RBFNNs Pattern Classifier and parameter coefficient is set by using Particle Swarm Optimization for model optimization. Proposed (2D)²PCA-based face pose classification performs recognition performance with PCA, (2D)²PCA and RBFNNs.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.51-54
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• 2008

In this paper, we propose a practical method for displaying 2D/True3D mixed contents in real-time. Many companies released their 3D display recently, but the costs of producing True3D contents are still very expensive. Since there are already a lot of 2D contents in the world and it is more effective to mix True3D objects into the 2D contents than making True3D contents directly, people became interested in mixing 2D/True3D contents. Moreover, real-time 2D/True3D mixing is helpful for 3D displays because the scenario of the contents can be easily changed on playback-time by adjusting the 3D effects and the motion of the True3D object interactively. In our system, True3D objects are rendered into multiple view-point images, which are composed with 2D contents by using depth information, and then they are multiplexed with pre-generated view masks. All the processes are performed on a graphics processor. We were still able to play a 2D/True3D mixed contents with Full HD resolution in real-time using a normal graphics processor.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.383-392
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• 2018

For prompt gamma ray imaging for biomedical applications and environmental radiation monitoring, we propose herein a multiple-scattering Compton camera (MSCC). MSCC consists of three or more semiconductor layers with good energy resolution, and has potential for simultaneous detection and differentiation of multiple radio-isotopes based on the measured energies, as well as three-dimensional (3D) imaging of the radio-isotope distribution. In this study, we developed an analytic simulator and a 3D image generator for a MSCC, including the physical models of the radiation source emission and detection processes that can be utilized for geometry and performance prediction prior to the construction of a real system. The analytic simulator for a MSCC records coincidence detections of successive interactions in multiple detector layers. In the successive interaction processes, the emission direction of the incident gamma ray, the scattering angle, and the changed traveling path after the Compton scattering interaction in each detector, were determined by a conical surface uniform random number generator (RNG), and by a Klein-Nishina RNG. The 3D image generator has two functions: the recovery of the initial source energy spectrum and the 3D spatial distribution of the source. We evaluated the analytic simulator and image generator with two different energetic point radiation sources (Cs-137 and Co-60) and with an MSCC comprising three detector layers. The recovered initial energies of the incident radiations were well differentiated from the generated MSCC events. Correspondingly, we could obtain a multi-tracer image that combined the two differentiated images. The developed analytic simulator in this study emulated the randomness of the detection process of a multiple-scattering Compton camera, including the inherent degradation factors of the detectors, such as the limited spatial and energy resolutions. The Doppler-broadening effect owing to the momentum distribution of electrons in Compton scattering was not considered in the detection process because most interested isotopes for biomedical and environmental applications have high energies that are less sensitive to Doppler broadening. The analytic simulator and image generator for MSCC can be utilized to determine the optimal geometrical parameters, such as the distances between detectors and detector size, thus affecting the imaging performance of the Compton camera prior to the development of a real system.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Current Optics and Photonics
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• v.6 no.6
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• pp.619-626
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• 2022

In this study, we develop a three-dimensional (3D) terahertz time-of-flight (THz-TOF) imaging technique with a large depth range, based on asynchronous optical sampling (ASOPS) methods. THz-TOF imaging with the ASOPS technique enables rapid scanning with a time-delay span of 10 ns. This means that a depth range of 1.5 m is possible in principle, whereas in practice it is limited by the focus depth determined by the optical geometry, such as the focal length of the scan lens. We characterize the spatial resolution of objects at different vertical positions with a focal length of 5 cm. The lateral resolution varies from 0.8-1.8 mm within the vertical range of 50 mm. We obtain THz-TOF images for samples with multiple reflection layers; the horizontal and vertical locations of the objects are successfully determined from the 2D cross-sectional images, or from reconstructed 3D images. For instance, we can identify metallic objects embedded in insulating enclosures having a vertical depth range greater than 30 mm. For feasible practical use, we employ the proposed technique to locate a metallic object within a thick chocolate bar, which is not accessible via conventional transmission geometry.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.167-176
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• 1999

The study about quantitative or qualitative analysis of object using digital image is being progressed actively with the development of the image medium and image process technique. But, it is very high that the dependency about image acquisition system of high resolution for image analysis of high accuracy and it is a equipment of high-price. In this study, I extracted the optimum condition of image enhancement by analyzing and enhancing the multiple images which were acquired by system of low-price. And I carried out the analysis of 3D accuracy by being applied the optimum condition of image enhancement. In the result of analysis of average 3D positioning error using law image and enhanced image which is acquired by applying the optimum condition of image enhancement, I could obtain the progressed accuracy about 10％ on the enhanced image.