• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1059-1068
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• 2016

The current operation method for the AVC (Automatic Vehicle Classification) equipment does not generate vehicle speed, traffic volume and vehicle type information when part of the sensors has failed. Inefficiency of current methods would not use the collected data from the normal sensor. In this study was conducted research on the calculating method at the traffic volume and vehicle speed in the sensor failure AVC equipment. The failure situation of the sensor was classified into 4 types. Calculating the traffic volume and vehicle speed information for each type, and accuracy of these informations were analyzed. Analysis results, traffic volume was possible to calculate a highly accurate value (accuracy: 100%, 98%, 97%). In the case of speed, the accuracy of the calculated speed value reaches a level that can be accepted sufficiently (RMSE value is less than 16.8). So, using the methodology proposed in this study are expected to be able to increase the operational efficiency of the AVC equipment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.93-104
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• 2023

Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.55-61
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• 2009

In order to observe the impact of a type of vehicles for traffic flows and pavement, vehicle classifications is conducted. Korean Ministry of Land, Transport and Maritime Affairs provides 12-type vehicle classifications on National expressways, National highways, and Provincial roads. Current AVC (Automatic Vehicle Classification) devices decide vehicle types comparing measurements of vehicle lengths, wheelbases, overhangs etc. to a reference table including those of all types of models. This study developed an algorithm for macroscopic vehicle classification which is less sensitive to tuning sensors and updating the reference table. For those characteristics, trend lines in vehicle lengths and wheelbases are employed. To assess the algorithm developed, vehicle lengths and wheelbases were collected from an AVC device. In this experiment, this algorithm showed the accuracy of 88.2 % compared to true values obtained from video replaying. Our efforts in this study are expected to contribute to developing devices for macroscopic vehicle classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2020-2025
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• 2006

H.264/AVC is newest video coding standard of the ITU-T Video coding Experts Group and the ISO/IEC Moving Picture Expets Group. Recently H.264/AVC has been adopted as a video compression standard in DMB and multimedia equipments. In this paper, we propose a H.264/AVC intra frame decoder which can minimize the memory usage and chip size. The proposed intra frame decoder is described in VHDL language and simulated in model_sim. It was verified in chip level by downloading to XCV1000E FPGA chip.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.1
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• pp.23-30
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• 2010

The H.264/AVC is increasingly used in broadcast video applications such as Internet Protocol television (IPTV), digital multimedia broadcasting (DMB) because of high compression performance. But the H.264/AVC coded video can be delivered to the widespread end-user equipment for MPEG-2 after transcoding between this video standards. This paper suggests a new transcoding algorithm for H.264/AVC to MPEG-2 transcoder that uses motion vector clustering in order to reduce the complexity without loss of video quality. The proposed method is exploiting the motion information gathered during h.264 decoding stage. To reduce the search space for the MPEG-2 motion estimation, the predictive motion vector is selected with a least distortion of the candidated motion vectors. These candidate motion vectors are considering the correlation of direction and distance of motion vectors of variable blocks in H.264/AVC. And then the best predictive motion vector is refined with full-search in ${\pm}2$ pixel search area. Compared with a cascaded decoder-encoder, the proposed transcoder achieves computational complexity savings up to 64% with a similar PSNR at the constant bitrate(CBR).

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.508-510
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• 2005

동영상 압축 표준인 H.264/AVC는 압축 효율을 높이기 위해 기존의 표준과는 다른 기법들을 사용함으로 압축률은 높였지만 보다 많은 계산량을 요구한다. 제한된 자원을 가진 임베디드 환경에서는 많은 계산량은 큰 문제점이 된다. DMB를 포함한 대부분의 경우는 이를 하드웨어적으로 구현을 하고 있지만 구현비용과 업데이트의 용의를 위해서 앞으로는 소프트웨어적으로도 구현이 가능해야 할 것이다. 본 논문에서는 H.264/AVC가 임베디드 환경에서 소프트웨어로 구현을 할 경우 그에 대한 성능 명가를 수행하기 위해 실제 임베디드 장비에서 H.264/AVC 복호기와 임베디드 그래픽 라이브러리를 사용해서 재생기를 구현하였고 다양한 종류의 영상을 재생시키는 실험을 하였다. 이러한 실험을 통해 임베디드 상에서 H.264/AVC 재생기는 QCIF 화면을 초당 3프레임 정도를 재생시키는 능력을 보였다. 이는 사용자측면에서는 동영상이라고 느낄 수 없을 정도의 성능이었다. 그러므로 임베디드 환경에서 H.264로 압축된 영상을 사용할 경우에는 H.264의 프로파일이나 레벨 조정 및 프레임 넘김 기법이 필요 할 것으로 추정한다.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.56-61
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• 2003

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1834-1843
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• 2016

DVRs are the most common recording and displaying devices used for surveillance. Video compression plays a key role in DVRs for saving storage; the video compression standard, H.264/AVC, has recently become the dominant choice for DVRs. DVRs require various display modes, such as fast-forward, backward play, and pause; these are called trick modes. The implementation of precise trick mode play requires a very high decoding capability or a very intelligent scheme in order to handle the high computation complexity. The complexity is increased in many surveillance applications where more than one camera is used to monitor multiple spots or to monitor the same area using various angles. An implementation of a trick mode play and a frame buffer management scheme for the hardware-based H.264/AVC codec for multi-channel is presented in this paper. The experimental results show that exact trick mode play is possible using a standard H.264/AVC video codec with keyframe encoding feature at the expense of bitstream size increase.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.143-144
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• 2015

최신 동영상 표준 코덱인 High Efficiency Video Coding (HEVC)는 기존의 H.264/AVC 보다 동일 화질 대비 최대 약 2배의 압축 성능을 보여준다. 이러한 성능을 얻기 위해 HEVC에는 다양한 압축 기술이 적용되었다. 그 예로, H.264/AVC에서는 인트라 예측 모드에서 9가지 예측 모드만을 사용한 반면 HEVC에서는 35가지의 모드를 이용해 화면 내 예측을 시행한다. HEVC에 적용된 다양한 기술들에 의해 부호화 복잡도가 증가하였고 복잡도를 줄이기 위해 다양한 고속 알고리즘이 연구되고 있다. 본 논문에서는 스크린 콘텐츠 영상 부호화에 적합한 고속 인트라 예측 알고리즘을 제안한다. 스크린 콘텐츠 영상이란 카메라를 이용해 촬영된 자연계 영상이 아닌 mobile phone, 방송 장비, 기타 전자 기기 등 컴퓨터 기술에 의해 생성되는 영상을 의미한다. 스크린 컨텐츠 영상은 자연계 영상과 달리 색의 변화가 전혀 없는 단순한 영역을 갖는 특성이 있다. 이러한 스크린 콘텐츠 영상의 특성을 반영하는 고속 알고리즘을 HEVC Test Model (HM) 16.6에 적용하였고, 스크린 컨텐츠 영상에서 25%의 속도 향상 결과를 얻을 수 있었다.