• Title/Summary/Keyword: 초해상화

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UHD Video Stitching Method for Enhanced User Experience (사용자 경험을 극대화한 UHD 영상 합성 기술)

  • Gankhuyag, Ganzorig;Hong, Eun Gi;Kim, Giyeol;Choe, Yoonsik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.7
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    • pp.1387-1394
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    • 2015
  • Along with the development of network transmission technology, the IPTV market is growing in fast pace. Additionally the UHD resolution broadcasting system along with user experience (UX) that provides better service to user has attracted attention recently since there are not enough research has been done with differentiated the UX that can enhance the UX yet. Therefore we proposed a low complexity syntax level image stitching implementation technique that run with multi-view services, which makes possibility to view multiple channel or video contents on the screen at the same time. Simulation results have demonstrated the liability and effectiveness of the proposed algorithm by showing that capability of generating more than 80 frames per second by stitching four Full-HD size videos into UHD frame.

A Study of Air Cargo Logistic System Process (항공물류 시스템 프로세스의 개선에 관한 연구)

  • Lee, Hwi-Young;Lee, Jae-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.9
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    • pp.179-187
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    • 2009
  • The national boundary's meanings turn to weak according to advent of Global enterprises. The place for design a product and marketing are separated to actual market. R&D is to the area where the knowledge activity is well, and low skilful product assembling is to the place the low wage is acceptable. It shows that the importance of net work structure. From early 90's, production system is diversified to markets where with the consumer as the central as multifarious items and creation new demands through consumer's participation into manufacturing process. This phenomenon show that logistics structures adapt to demand of technical variation, and the development of e-business with VAN(:value added network) and EDI(:Electronic data interchange) prove it. This study tried to analyze utilitarian assay about systems those land, sea, air logistics through documents research, and this study also present the direction of logistics system of airline company and goal of development on the based to the model of domestic airline company accordingly.

Optimal Estimation of the Peak Wave Period using Smoothing Method (평활화 기법을 이용한 파랑 첨두주기 최적 추정)

  • Uk-Jae, Lee;Byeong Wook, Lee;Dong-Hui, Ko;Hong-Yeon, Cho
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.34 no.6
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    • pp.266-274
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    • 2022
  • In this study, a smoothing method was applied to improve the accuracy of peak wave period estimation using the water surface elevation observed from the Oceanographic and Meteorological Observation Tower located on the west coast of the Korean Peninsula. Validation of the application of the smoothing method was per- formed using variance of the surface elevation and total amount wave energy, and then the effect on the application of smoothing was analyzed. As a result of the analysis, the correlation coefficient between variance of the surface elevation and total amount wave energy was 0.9994, confirming that there was no problem in applying the method. Thereafter, as a result of reviewing the effect of smoothing, it was found to be reduced by about 4 times compared to the confidence interval of the existing estimated spectrum, confirming that the accuracy of the estimated peak wave period was improved. It was found that there was a statistically significant difference in proba- bility density between 4 and 6 seconds due to the smoothing application. In addition, for optimal smoothing, the appropriate number of smoothings according to the significant wave height range was calculated using a statistical technique, and the number of smoothings was found to increase due to the unstable spectral shape as the significant wave height decreased.

Implementation of a Person Tracking Based Multi-channel Audio Panning System for Multi-view Broadcasting Services (다시점 방송 서비스를 위한 사용자 위치추적 기반 다채널 오디오 패닝 시스템 구현)

  • Kim, Yong-Guk;Yang, Jong-Yeol;Lee, Young-Han;Kim, Hong-Kook
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.150-157
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    • 2009
  • In this paper, we propose a person tracking based multi-channel audio panning system for multi-view broadcasting services. Multi-view broadcasting is to render the video sequences that are captured from a set of cameras based on different viewpoints, and multi-channel audio panning techniques are necessary for audio rendering in these services. In order to apply such a realistic audio technique to this multi-view broadcasting service, person tracking techniques which are to estimate the position of users are also necessary. For these reasons, proposed methods are composed of two parts. The first part is a person tracking method by using ultrasonic satellites and receiver. We could obtain user's coordinates of high resolution and short duration about 10 mm and 150 ms. The second part is MPEG Surround parameter-based multi-channel audio panning method. It is a method to obtain panned multi-channel audio by controlling the MPEG Surround spatial parameters. A MUSHRA test is conducted to objectively evaluate the perceptual quality and measure localization performance using a dummy head. From the experiments, it is shown that the proposed method provides better perceptual quality and localization performance than the conventional parameter-based audio panning method. In addition, we implement the prototype of person tracking based multi-view broadcasting system by integrating proposed methods with multi-view display system.

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A license plate area segmentation algorithm using statistical processing on color and edge information (색상과 에지에 대한 통계 처리를 이용한 번호판 영역 분할 알고리즘)

  • Seok Jung-Chul;Kim Ku-Jin;Baek Nak-Hoon
    • The KIPS Transactions:PartB
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    • v.13B no.4 s.107
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    • pp.353-360
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    • 2006
  • This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

Experimental Implementation of Continuous GPS Data Processing Procedure on Near Real-Time Mode for High-Precision of Medium-Range Kinematic Positioning Applications (고정밀 중기선 동적측위 분야 응용을 위한 GPS 관측데이터 준실시간 연속 처리절차의 실험적 구현)

  • Lee, Hungkyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.3
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    • pp.31-40
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    • 2017
  • This paper deals with the high precision of GPS measurement reduction and its implementation on near real-time and kinematic mode for those applications requiring centimeter-level precision of the estimated coordinates, even if target stations are a few hundred kilometers away from their references. We designed the system architecture, data streaming and processing scheme. Intensive investigation was performed to determine the characteristics of the GPS medium-range functional model, IGS infrastructure and some exemplary systems. The designed system consisted of streaming and processing units; the former automatically collects GPS data through Ntrip and IGS ultra-rapid products by FTP connection, whereas the latter handles the reduction of GPS observables on static and kinematic mode to a time series of the target stations' 3D coordinates. The data streaming unit was realized by a DOS batch file, perl script and BKG's BNC program, whereas the processing unit was implemented by definition of a process control file of BPE. To assess the functionality and precision of the positional solutions, an experiment was carried out against a network comprising seven GPS stations with baselines ranging from a few hundred up to a thousand kilometers. The results confirmed that the function of the whole system properly operated as designed, with a precision better than ${\pm}1cm$ in each of the positional component with 95% confidence level.

Comparison of Seismic Data Interpolation Performance using U-Net and cWGAN (U-Net과 cWGAN을 이용한 탄성파 탐사 자료 보간 성능 평가)

  • Yu, Jiyun;Yoon, Daeung
    • Geophysics and Geophysical Exploration
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    • v.25 no.3
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    • pp.140-161
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    • 2022
  • Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

A Proposed Algorithm and Sampling Conditions for Nonlinear Analysis of EEG (뇌파의 비선형 분석을 위한 신호추출조건 및 계산 알고리즘)

  • Shin, Chul-Jin;Lee, Kwang-Ho;Choi, Sung-Ku;Yoon, In-Young
    • Sleep Medicine and Psychophysiology
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    • v.6 no.1
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    • pp.52-60
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    • 1999
  • Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

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Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

Usefulness Comparative Experimental Study of the CT and MR Imaging in the Dog Clonorchiasis (잡견 간흡충증의 전산화단층촬영과 자기공명영상의 유용성에 관한 실험적 연구)

  • Goo, Eun-Hoe;Kweon, Dae-Cheol;Kim, Dong-Sung;Choi, Chun-Kyu
    • Journal of radiological science and technology
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    • v.26 no.3
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    • pp.33-39
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    • 2003
  • Purpose : Be aware of clinical possibilities on image quality by comparison of contrast-enhanced dynamic CT and MR imaging applied of MIP technique after the experimentally induced clonorchasis infection in dogs. Materials and Method : Twenty mongrel dogs prepared in zoo-laboratory were followed up with serial CT scans and MR imaging for 13 weeks after the experimental infection in liver. Two-phase helical CT was acquired in the supine position with the following scanning parameters. After the injection of contrast material, the arterial phase was initiated using a bolus-racking method. The portal phase scan was started 15 seconds after the arterial phase scan. CT protocol was determined after single level dynamic scans. MR imaging used the CP body coil and images get a 2D image using HASTE, FLASH, TSE pulse sequence. Bile duct MR imaging were obtained in three plans. Then each image was post processed by using target MIP algorithm. Two experimentation above, as a method of evaluation, one pathologist, three radiologist and five radiological technologist were analyzed visually for evaluation of following findings, enhancement of the bile duct wall, dilatation of bile duct tip, liver parenchyma, background suppression. Results : Five dogs was died of a disease after the infection, the rest one else shows the chronic dilatation of the intrahepatic bile duct with CT and MR imaging. Contrast administration of CT shows the contrast-enhanced of the bile duct walls with live parenchyma. MR imaging calculated of CNR and CR from pulse sequence for comparative evaluation and shows the pattern of the intrahepatic bile duct, dilatation of bile duct tip using MIP technique. CNR of the clonorchiasis, HASTE was $16{\pm}0.83$, TSE $7.06{\pm}3.0$, FLASH $1.19{\pm}0.2$ and CR, HASTE was 73.3%, TSE 62.3%, FLASH 6.4%. Conclusion : CT and MR imaging is very usefulness in diagnosis of dog clonorchiasis.

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