• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.11
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• pp.27-33
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• 2011

Recently many display devices support the digital display interface as display market growth. DisplayPort is a next generation display interface at the PC, projector and high definition content applications in more widely used connection solution development. This paper implements multiple streams based on the behavior of the main link that is suitable for the display port v1.1a standard. The limit point of Displayport, interface between the Sink Device and Sink Device is also implemented. And two or more differential image data are enable to output the result through four Lanes stated in display port v1.1a, of two or more display devices without the addition of a separate Lane. The Multiple Video Streaming Controller is implemented with 6,222 ALUTs and 6,686 register, 999,424 of block memory bits synthesized using Quartus II at Altera Audio/Video Development board (Stratix II GX FPGA Chip).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1363-1368
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• 2016

Fast rendering speed is one of key functions to provide realistic scenes in flight simulator. However, since flight simulator mostly operates with high volume terrain data, rendering speed is reduced and changed very rapidly when it handles file containing too much vertexs. So, previous schemes make use of Level of Details (LOD) scheme to prevent this problem. But, since LOD is applied after the large number of vertexs are detected, transition between scenes is not completely smooth. To solve this problem, in this paper, we propose a new dynamic LOD scheme which controls LOD level in advance through prediction of vertex overload. To verify the proposed scheme, we implement the proposed scheme in our flight simulation through OpenSceneGraph(OSG) and identify the reduced number of vertexs and enhanced Frame Per Second (FPS) by comparing real data with predicted one.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.829-846
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• 2018

Crop monitoring can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. But, traditional monitoring has used field measurements involving destructive sampling and laboratory analysis, which is costly and time consuming. Unmanned Aerial vehicle (UAV) could be effectively applied in a field of crop monitoring for estimation of cultivated area, growth parameters, growth disorder and yield, because it can acquire high-resolution images quickly and repeatedly. And lower flight altitude compared with satellite, UAV can obtain high quality images even in cloudy weather. This study examined the possibility of utilizing UAV in the field of crop monitoring and was to suggest the application method for production of crop status information from UAV.

• Journal of the Korean earth science society
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• v.26 no.1
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• pp.58-65
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• 2005

Homomorphic filtering improves image by enhancing high components and reducing low components in the Sequency domain based on FFT, as one of useful digital image processing techniques. In this study, the application program f3r homomorphic filtering was developed. Using this program, satellite imageries and geophysical image such as magnetic image data were processed and their results were analyzed. In case of applying to other techniques suck as histogram equalization and kernel-based masking f3r the same purpose. they often cause the slight distortion of boundary or overall change of brightness values on the whole image. Whereas. homomorphic filtering has ability to enhance selectively detailed components in a target image. Therefore. this technique can be effectively used for extraction or separation of complex types of characteristics contained in the satellite imagery. In addition, this technique would be applicable to investigate anomalous zone in various geophysical image data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.11
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• pp.101-106
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• 2005

A ground penetrating image radar (GPR) using an ultra wideband (UWB)impulse waveform is developed for non destructive detection of metallic pipelines buried under the ground. Dielectric constant of test field is measured and then a GPR system is designed for better detection up to 1 meter deep. By considering total path loss, volume of complete system, and resolution, upper and lower frequencies are chosen. First, a UWB impulse for the frequency bandwidth of the impulse is chosen with rising time less than 1 ns, and then compact planar UWB dipole antenna suitable for frequency bandwidth of a UWB impulse is designed. Also, to receive reflected signals, a digital storage oscilloscope is used. For measurement, a monostatic technique and a migration technique are used. For visualizing underground targets, simple image processing techniques of A-scan removal and B-scan average removal are applied. The prototype of the system is tested on a test field in wet clay soil and it is shown that the developed system has a good ability in detecting underground metal objects, even small targets of several centimeters.

• Korean Journal of Ecology and Environment
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• v.44 no.1
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• pp.58-65
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• 2011

This study aims to investigate the settling velocity of aggregates of cohesive sediment (floc) and its relationship with sediment size, density and fractal dimension. A system of commercial camera and macro-lens is used for the experiment. Through the image-analysis technique, the image taken by the camera system is analyzed. For the experiment, kaolinite and a natural sediment sampled at Lake Apopka in Florida have been tested. From this study, it is known that kaolinite and Lake Apopka sediments show different behaviors mainly depending on the organic matter content. Samples of kaolinite with less organic contents show a more definite trend to follow a fractal theory and relatively strong relationships between the settling velocity, density, fractal dimension and floc size compared to the Lake Apopka sediments rich in organics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.641-642
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• 2013

This research implemented Geostationary Ocean Color Imager (GOCI) observation satellite imagery visualization system on a large high-resolution tiled display. This system is designed to help users observe or analyze satellite imagery more effectively on the tiled display using multi-touch and Kinect motion gesture recognition interaction. We developed the multi-scale image loading and rendering technique for the massive amount of memory management and smooth rendering for GOCI satellite imagery on the tiled display. In this system, the unit of time corresponding to the selected date of the satellite images are sequentially displayed on the screen. Users can zoom-in, zoom-out, move the imagery and select some buttons to trigger functions using both multi-touch or Kinect gesture interaction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.699-706
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• 2008

H.264/AVC is a new international standard for the compression of video images, in which a deblocking filter has been adopted to remoye blocking artifacts. This paper proposes an efficient architecture of deblocking filter in H.264/AVC. By making good use of data dependence between neighboring $4{\times}4$ blocks, the memory sire is reduced and the throughput of the deblocking filter processing is increased. The designed deblocking filter further enhances the parallelism by simultaneously executing horizontal and vertical filtering within a macroblock in pipeline method and adopting overlap between macroblocks. The implementation result shows that the proposed architecture enhances the performance of deblocking filter processing from 1.75 to 4.23 times than that of the conventional deblocking filter. Hence the Proposed architecture of deblocking filter is able to perform real-time deblocking in high-resolution($2048{\times}1024$) video applications.

• Smart Media Journal
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• v.9 no.4
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• pp.134-143
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• 2020

Vehicle License Plate Recognition is one of the approaches for transportation and traffic safety networks, such as traffic control, speed limit enforcement and runaway vehicle tracking. Although it has been studied for decades, it is attracting more and more attention due to the recent development of deep learning and improved performance. Also, it is largely divided into license plate detection and recognition. In this study, experiments were conducted to improve license plate detection performance by utilizing various object detection methods and WPOD-Net(Warped Planar Object Detection Network) model. The accuracy was improved by selecting the method of detecting the vehicle(s) and then detecting the license plate(s) instead of the conventional method of detecting the license plate using the object detection model. In particular, the final performance was improved through the process of removing noise existing in the image by using the Fast-SRGAN model, one of the Super-Resolution methods. As a result, this experiment showed the performance has improved an average of 4.34% from 92.38% to 96.72% compared to previous studies.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.