• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.892-904
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• 2008

As a video encoding in resource constrained environments such as sensor networks has become an important issue, DVC(Distributed Video Coding) has been intensively investigated as a solution for light weighted video encoding problem. Known as one of the representative schemes of DVC, the Wyner-Ziv coding generates side information of current frame only at decoder, using correlation among frames, and reconstructs video through noise elimination on the side information using channel code. Accordingly, the better quality of side information brings less channel noise, thus attains better coding performance of the Wyner-Ziv coder. However, since it is hard for decoder to generate an accurate side information without any information of original frame, a method to successively improve side information using successively decoded original frame, based on decoding reliability, was previously developed. However, to improve side information from decoding results, not only an error rate of the decoding result as a reliability, but also the amount of reliable information from the decoding result is important. Therefore, we propose TDWZ(Transform-domain Wyner-Ziv coding) with successively improving side information based on decoding reliability considering not only an error rate but also the amount of reliable information of the decoding results. Our experiment shows the proposed method gains average PSNR up to 1.7 dB over the previous TDWZ, that is without successive side information improvement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.11-21
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• 2008

In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.48-57
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• 2013

Smartphones provide users with environment for communication and sharing information and at the same time play an important role of mobile technology and mobile art development. Smartphone technology-related researches are being accelerated especially with the advent of mobile Augmented Reality(AR) age, but the studies on user participation that is essential for AR content industry were insufficient. In that regard, the assistance from mobile art area that has already developed these characteristics is essential. Thus, this article is to classify mobile art that has not been studied a lot domestically into feature phone usage and smartphone usage and to analyze each example case with the three most used methods. The usage of feature phones which use the sound and images of mobile devices can be divided into three: installation and performing methods, single channel video art method and five senses communication method. On the other hand, the usage of smartphones that use sensors, cameras, GPS and AR can be divided into location-based AR, marker-based AR and markerless AR. Also, as a result of examining mobile AR content utilization technology by industries, combined methods are utilized; tourism and game-related industries use location-based AR, education and medicine-related industries use marker-based AR, and shopping-related industries use markerless AR. The development of AR content industry is expected to be accelerated with mobile art that makes use of combined technology method and constant communication method through active participation of users. The future development direction of mobile AR industry is predicted to have minimized HMD, integration of hologram technology and artificial intelligence and make the most of big data and social network so that we could overcome the technological limitation of AR.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.13-13
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• 2023

디지털 기술은 오늘날 플랫폼과 디지털 트윈의 기술도입을 통해 현실 세계를 네트워크와 가상세계와의 연결이 통합되어진 가상 현실 세계의 입문 도약이다. 현실에서 가상현실의 사이의 디지털 전환(digital transformation)에는 디지털 기술과 솔루션을 비즈니스의 모든 영역에 통합하는 것이 포함된다. 이러한 디지털 전환의 핵심은 데이터에 관한 것이며, 데이터를 활용하여 가치를 창출하고 고객경험과 비즈니스 영역을 극대화하는 방식을 제공한다. 최적의 데이터를 제공하기 위한 플랫폼과 가상 현실세계 구현을 위한 디지털 트윈의 상호연계 관한 기본 개념은 데이터 수집, 데이터 분석, 데이터 시각화 및 데이터 보고와 같은 데이터 비즈니스이다. 현장 데이터는 디지털 양식을 통해 수집, 기록, 저장된다. 현장 IoT 기반 데이터(사진 및 비디오 매체 등)는 지속적으로 수집되고 종종 다른 데이터베이스에 저장되지만 지리 공간적 위치에 연결되지 않는다. 모든 디지털 발전을 조화시키고 지하수 데이터에서 더 빠른 이해를 도출하기 위해서는 디지털 트윈이 시작되어야 한다. 단일 지하수플랫폼에서 현장 조건을 시각화하고 실시간 데이터를 스트리밍하며, 과거 3D 데이터와 상호작용하여지질 또는 지화학 데이터를 선택적 사용을 위해 지하수 플랫폼과 디지털 트윈이 연계되어야 한다. 데이터를 디지털 정보모델과 연결하면 디지털 트윈에 생명을 불어넣을 수 있지만 디지털 트윈의 가치를 극대화하려면 여전히 데이터 플랫폼 서비스와 전달 방식을 선택해야 한다. 지하수 플랫폼동시성을 갖는 디지털 트윈은 정적 및 동적 데이터를 저장하는 데이터베이스 또는 크라우드 서비스에서 데이터를 가져오는 API(애플리케이션 프로그래밍 인터레이스), 디지털 트윈을 위한 호스팅 공간, 디지털 대상을 구축하는 소프트웨어, 구성 요소 간 읽기/쓰기를 위한 스크립트, chatGPT 및 API를 활용할 수 있다. 이를 통해 수집된 데이터의 실시간 양방향 통신기술인 지하수 플랫폼 기술을 활용하여 디지털 트윈을 적용하고 완성할 수 있고, 이를 지하수 분야에도 그대로 적용할 수 있다. 지하수 분야의 디지털 트윈 기술의 근간은 지하수 모니터링을 위한 관측장치와 이를 활용한 지하수 플랫폼의 구축 및 양방향 자료전송을 통한 분석 및 예측기술이다. 특히 낙동강과 같이 유역면적이 넓고 유역 내 지자체가 많아 이해관계가 다양하며, 가뭄과 홍수/태풍 등 기후위기에 따른 극한 기상이변가 자주 발생하고, 또한 보 및 하굿둑 개방 등 정부정책 이행에 따른 민원이 다수 발생하는 지역의 경우 하천과 유역에 대한 지하수 플랫폼과 디지털 트윈의 동시성 기술적용 시 지하수 데이터에 대한 고려가 반드시 수반되어야 한다.