• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.303-308
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• 2018

In copyright rights of the digital image, copyright holders need to protect copyrights and improve the improvement of copyright laws through accurate understanding of copyright laws, and also to improve the effectiveness of copyright rights of copyright holders and the effectiveness of users' rights. First of all, the scope of the study is based on the case of recognition of the scope of the identity of the same scope and the copyright on the copyright law of the digital image, and the application of the image of the image of the image-writing image and the use of image artifacts based on the image copyright classification system suitable for the user's application.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.714-719
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• 2014

A pico-projector is a compact and mobile projector that has an infinite focus. We apply the pico-projector to a projection-type integral imaging system, which can expand the image depth to form multiple central depth planes. In a projection-type integral imaging system, the image flipping problem arises because the expanded elemental images pass through a lens array. To solve this problem, we propose the ray tracing of a pico-projector at a central depth plane and compensate the elemental image using a pixel-mapping process. Experiments to verify the proposed method are performed, and the results are presented.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.19-29
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• 2008

Underwater acoustic(UWA) communication is one of the most difficult field in terms of severe channel environments such as multipath propagation, high temporal and spatial variability of channel conditions. Therefore, it is important to model and analyze the characteristics of underwater acoustic channel such as multipath propagation, transmission loss, reverberation, and ambient noise. In this paper, UWA communication channel is modeled with a ray tracing method and applied to image transmission. Quadrature phase shift keying(QPSK) and multichannel decision feedback equalizer(DFE) are utilized as phase-coherent modulation method and equalization technique, respectively. The objective is to improve the performance of the image transmission using vertical sensor array instead of single sensor in the viewpoint of bit error rate(BER), constellation diagram, and received image quality.

• The Journal of Advanced Prosthodontics
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• v.6 no.4
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• pp.259-265
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• 2014

PURPOSE. The purpose of this study was to develop a dental image processing system using a three-dimensional (3D) camera and stereovision technology. The reliability of the system for measuring axial wall convergence angles was evaluated. MATERIALS AND METHODS. The new system predicted 3D coordinate points from 2D images and calculated distances and angles between points. Two examiners measured axial wall convergence angles for seven artificial abutments using a traditional tracing-based method (TBM) and the stereovision-based method (SVBM). Five wax abutment models of simplified abutment forms were made and axial wall convergence angles of wax models were measured by both methods. The data were statistically analyzed at the level of significance, 0.05. RESULTS. Intraclass correlation coefficients showed excellent intra-examiner and inter-examiner reliabilities for both methods. Bland-Altman plots and paired t-tests showed significant differences between measurements and true values using TBM; differences were not significant with SVBM. CONCLUSION. This study found that the SVBM reflected true angle values more accurately than a TMB and illustrated an example of 3D computer science applied to clinical dentistry.

• Journal of KIISE
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• v.43 no.8
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• pp.835-840
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• 2016

Monte Carlo ray tracing has been widely used for simulating a diverse set of photo-realistic effects. However, this technique typically produces noise when insufficient numbers of samples are used. As the number of samples allocated per pixel is increased, the rendered images converge. However, this approach of generating sufficient numbers of samples, requires prohibitive rendering time. To solve this problem, image filtering can be applied to rendered images, by filtering the noisy image rendered using low sample counts and acquiring smoothed images, instead of naively generating additional rays. In this paper, we proposed a Stein's Unbiased Risk Estimator (SURE) based $\grave{A}$-Trous wavelet to filter the noise in rendered images in a near-interactive rate. Based on SURE, we can estimate filtering errors associated with $\grave{A}$-Trous wavelet, and identify wavelet coefficients reducing filtering errors. Our approach showed improvement, up to 6:1, over the original $\grave{A}$-Trous filter on various regions in the image, while maintaining a minor computational overhead. We have integrated our propsed filtering method with the recent interactive ray tracing system, Embree, and demonstrated its benefits.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

• Current Optics and Photonics
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• v.5 no.5
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• pp.524-531
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• 2021

In an integral-imaging microscopy (IIM) system, a microlens array (MLA) is the primary optical element; however, surface errors impede the resolution of a raw image's details. Calibration is a major concern with regard to incorrect projection of the light rays. A ray-tracing-based calibration method for an IIM camera is proposed, to address four errors: MLA decentering, rotational, translational, and subimage-scaling errors. All of these parameters are evaluated using the reference image obtained from the ray-traced white image. The areas and center points of the microlens are estimated using an "8-connected" and a "center-of-gravity" method respectively. The proposed approach significantly improves the rectified-image quality and nonlinear image brightness for an IIM system. Numerical and optical experiments on multiple real objects demonstrate the robustness and effectiveness of our proposed method, which achieves on average a 35% improvement in brightness for an IIM raw image.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.631-634
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• 1999

In this work, a new algorithm for canceling MRI artifact in the image plane is presented. In the conventional approach, the motions in the X(readout) direction and Y(the phase encoding) direction are estimated simultaneously. However, the feature of each X and Y directional motion is different. First, we notice that the X directional motion corresponds to a shift of the X directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to X axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the X directional motion is canceled by shifting the spectrum in inverse direction. Next, the Y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by simulations.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1075-1078
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• 1999

In this study, a new algorithm for canceling MRI artifacts through the translational motion of image plane is presented. Bloating is often makes problems in a clinical diagnosis. Assuming that the head moves up and down due to breathing, rigid translational motions in only y(phase encoding axis) direction is treated. First, we notice that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to x axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the x directional motion is canceled by shifting the spectrum in inverse direction. Next, the y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. Finally, the effectiveness of this algorithm is shown by using a phantom with simulated motions.