• Journal of Broadcast Engineering
• /
• v.10 no.3
• /
• pp.413-421
• /
• 2005

As the population of HDTV is growing, among many useful features of modern set top boxes (STBs) or digital video recorders (DVRs), video browsing, visual bookmark, and picture-in-picture capabilities are very frequently required. These features typically employ reduced-size versions of video frames, or thumbnail images. Most thumbnail generation approaches generate DC images directly from a compressed video stream. A discrete cosine transform (DCT) coefficient for which the frequency is zero in both dimensions in a compressed block is called a DC coefficient and is simply used to construct a DC image. If a block has been encoded with field DCT, a few AC coefficients are needed to generate the DC image in addition to a DC coefficient. However, the bit length of a codeword coded with variable length coding (VLC) cannot be determined until the previous VLC codeword has been decoded, thus it is required that all codewords should be fully decoded regardless of their necessary for DC image generation. In this paper, we propose a method especially for fast DC image generation from an I-frame using multiple-symbol lookup table (mLUT). The experimental results show that the method using the mLUT improves the performance greatly by reducing LUT count by 50$\%$.

• Journal of Broadcast Engineering
• /
• v.6 no.3
• /
• pp.246-259
• /
• 2001

Due to recent rapid deployment of Internet streaming service and digital broadcasting service, the issue of how to efficiently support streaming workload in so called "Internet Home Appliance" receives prime interests from industry as well as academia. The underlying dilemma is that it may not be feasible to put cutting edge CPU, boards, disks and other peripherals into that type of device. The primary reason is its cost. Usually, Internet Home Appliances has its dedicated usage, e.g. Internet Radio, and thus it does not require high-end CPU nor high-end Va subsystem. The same reasoning applies to I/O subsystem. In Internet Home Appliances dedicated to handle compressed moving picture, it is not equipped with high end SCSI disk with fast rotational speed. Thus, it is mandatory to devise elaborate software algorithm to exploit the available hardware resources and maximize the efficiency of the system. This paper presents our experiences in the design and implementation of a new multimedia file system which can efficiently deliver the required disk bandwidth for a periodic I/O workload. We have implemented the file system on the Linux operating system, and examined itsperformance under streaming I/O workload. The results of the study show that the proposed file system exhibits superior performance than the Linux Ext2 file system under streaming I/O workload. The result of this work not only contribute to advance the state f art file system technology for multimedia streaming but also put forth the software which is readily available and can be deployed. deployed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2003.11a
• /
• pp.75-78
• /
• 2003

MPEG-4 표준은 저작자가 정지영상, 텍스트, 2D/3D 그래픽스, 오디오, 심지어 임의형의 비디오 등과 같이 다양한 형태의 객체들을 개별적으로 구성하고 이들을 시/공간자적으로 다루기 용이하게 해 준다. 이와 같은 객체 기반 코딩 특성에 의해서 대화형 방송 콘텐츠를 제작하는데 가장 유용한 방식으로 고려할 수 있다. 피러나, 콘텐츠의 제작, 전송, 소비 관전에서 고려해 달 때, 콘텐츠 제작자 또는 저작권자의 보호 및 관리가 필요하게 되었다. 이에 따라 최근에는 OPIMA (Open Platform Initiative for Multimedia Access), SDMI (Secure Digital Music Initiative) and MPEG(Moving Picture Expert Group) OPIMATfMr(Intellectual Property Management & Protection)와 같은 국제 표준 단체들이 콘텐츠 보호 및 관리에 대한 관심을 가지게 되었다. 특히, MPEG의 경우에 MPEG-4 IPMP를 표준화하여 디지털 콘텐츠와 저작권에 대한 보호를 체계적이고 효과적으로 다루는 연구를 가장 활발히 해오고 있다. 이 논문에서 우리는 MPEG-4 콘텐츠 저작자가 MPEG-4 규격에 맞게 보호화 된 객체 기반 방송용 콘텐츠를 쉽고 편리하게 제작학 수 있도록 하기 위한 MPEG씨 콘텐츠 및 저자권 보호를 위한 MPEG-4 IPMP 저작 도구를 제안하고자 한다. 제안한 MPEG-4 콘텐츠 및 저작권 보호 저작 도구는 저작자에게 친근한 사용자 인터페이스를 제공하여 편집 및 수정이 용이한 텍스트 포맷인 IPMP회된 XMT(extensible Mpeg-4 Textual format) 파일을 생성한다. 또한, 콘텐츠 전송 및 저장의 효율성을 위해 이진 포멧인 IPMP화된 MP4 파일을 생성할 수 있다.으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.우 $23.87\%$($18.00\~30.91\%$), 갑폭 $23.99\%$($17.82\~30.48\%$), 체중 $91.51\%$($58.86\~129.14\%$)이였으며 성장율은 사육 온도구간별 차는 없었다.20 km 까지의 지점들(지점 2에서 지점 6)에서 매우 높은 값을 보이며 이는 조석작용으로 해수와 담수가 강제혼합되면서 표층퇴적물이 재부유하기 때문이라고 판단된다. 영양염류는 월별로 다소의 차이는 있으나, 대체적으로 지점 1과 2에서 가장 낮고, 상류로 갈수록 점차 증가하며 지점 7 상류역이 하류역에 비해 높은 농도이다. 월별로는 7월에 규산염, 용존무기태질소 및 암모니아의 농도가 가장 높은 반면에 용존산소포화도는 가장 낮다. 그러나 지점 14 상류역에서는 5월에 측정한 용존무기태질소, 암모니아, 인산염 및 COD 값이 7월보다 다소 높거나 비슷하다. 한편 영양염류와 COD값은 대체적으로 8월에 가장 낮으나 용존산소포화도는 가장 높다.출조건은 $100^{\circ}C$에서 1분간의 고온단시간 추출이 적합하였다. 증가를 나타내었는데, 저장기간에 따른 물성의 변화는 숭어에 비하여 붕장어가 적었다.양식산은 aspartic acid 및 proline이 많았다. 또한 잉어는 천연산이

• Journal of Broadcast Engineering
• /
• v.15 no.1
• /
• pp.29-39
• /
• 2010

This paper presents and analyzes laboratory test results of distributed translator (DTxR) for distributed frequency network (DFN) in the ATSC (Advanced Television Systems Committee) terrestrial digital TV broadcasting system. The DTxR laboratory test is classified to receiving part test and transmitting part test. The receiving part test includes dynamic range, random noise, single echo, and adjacent channel interference. The transmitting part test includes quality of output signal (out-of channel emission, quality of transmitting signal, and phase noise), frequency synchronization among output signals, and TxID (Transmitter Identification) signal's affect to the legacy receiver. By the laboratory test results, the receiving part of DTxR eliminates average -2.5 dB of single echo and has average 17.5 dB at TOV (Threshold of Visibility) under random noise environment. In addition, the transmitting part of DTxR satisfies the specification of US FCC (Federal Communications Commission), and frequency difference among DTxR output signals is less than 0.001 Hz.

• Journal of Broadcast Engineering
• /
• v.17 no.1
• /
• pp.73-80
• /
• 2012

Recently, medical equipments are developed and used for diagnosis or studies. In addition, demand of techniques which automatically deal with three dimensional medical images obtained from the medical equipments is growing. One of the techniques is automatic bone segmentation which is expected to enhance the diagnosis efficiency of osteoporosis, fracture, and other bone diseases. Although various researches have been proposed to solve it, they are unable to be used in practice since a size of the medical data is large and there are many low contrast boundaries with other tissues. In this paper, we present a fast and accurate automatic framework for bone segmentation based on multi-resolutions. On a low resolution step, a position of the bone is roughly detected using constrained branch and mincut which find the optimal template from the training set. Then, the segmentation and the registration are iteratively conducted on the multiple resolutions. To evaluate the performance of the proposed method, we make an experiment with femur and tibia from 50 test knee magnetic resonance images using 100 training set. The proposed method outperformed the constrained branch and mincut in aspect of segmentation accuracy and implementation time.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.1076-1084
• /
• 2019

In this paper, we introduced a system that extracts metadata by recognizing characters and objects in media using deep learning technology. In the field of broadcasting, multimedia contents such as video, audio, image, and text have been converted to digital contents for a long time, but the unconverted resources still remain vast. Building media archives requires a lot of manual work, which is time consuming and costly. Therefore, by implementing a deep learning-based metadata generation system, it is possible to save time and cost in constructing media archives. The whole system consists of four elements: training data generation module, object recognition module, character recognition module, and API server. The deep learning network module and the face recognition module are implemented to recognize characters and objects from the media and describe them as metadata. The training data generation module was designed separately to facilitate the construction of data for training neural network, and the functions of face recognition and object recognition were configured as an API server. We trained the two neural-networks using 1500 persons and 80 kinds of object data and confirmed that the accuracy is 98% in the character test data and 42% in the object data.

• Journal of Broadcast Engineering
• /
• v.28 no.1
• /
• pp.31-41
• /
• 2023

Directly converting the focal depth and image size of computer-generated-hologram (CGH), which is obtained by calculating the interference pattern of light from the 3D image, is known to be quite difficult because of the less similarity between the CGH and the original image. This paper proposes a method for separately converting the each of focal length of the given CGH, which is composed of multi-depth images. Firstly, the proposed technique converts the 3D image reproduced from the CGH into a Light-Field (LF) image composed of a set of 2D images observed from various angles, and the positions of the moving objects for each observed views are checked using an object detection algorithm YOLOv5 (You-Only-Look-Once-version-5). After that, by adjusting the positions of objects, the depth-transformed LF image and CGH are generated. Numerical simulations and experimental results show that the proposed technique can change the focal length within a range of about 3 cm without significant loss of the image quality when applied to the image which have original depth of 10 cm, with a spatial light modulator which has a pixel size of 3.6 ㎛ and a resolution of 3840⨯2160.

• Journal of Broadcast Engineering
• /
• v.28 no.1
• /
• pp.55-78
• /
• 2023

The fringe pattern obtained through a DHM (Digital Holographic Microscopy) contains the thickness information of the sample. However, there is a disadvantage that the data capacity is large. Therefore, a compression method that can reduce the data size while minimizing damage to the thickness information of the sample contained in the fringe pattern is required. This paper presents the phase compression method and confirmed through experiments that the phase compression method is more efficient that the fringe pattern compression method used in JPEG Pleno Holography. As a result of evaluation using RMSE, BD-Rate and PSNR the phase compression method showed up to 92.39% improvement in performance than the fringe pattern compression method. In addition, experiment were conducted under various conditions to compare and analyze the compression performance for each condition. In the case of the fringe pattern compression method, it includes not only the phase information for calculating the thickness of the sample but also other information, whereas the phase compression method compresses only the phase information after removing unnecessary information from the fringe pattern. It is judged to have high performance.

• Journal of Broadcast Engineering
• /
• v.28 no.3
• /
• pp.285-292
• /
• 2023

Recently, the impact of fine dust on health has become a major topic. Fine dust is dangerous because it can penetrate the body and affect the respiratory system, without being filtered out by the mucous membrane in the nose. Since fine dust is directly related to the industry, it is practically impossible to completely remove it. Therefore, if the concentration of fine dust can be predicted in advance, pre-emptive measures can be taken to minimize its impact on the human body. Fine dust can travel over 600km in a day, so it not only affects neighboring areas, but also distant regions. In this paper, wind direction and speed data and a time series prediction model were used to predict the concentration of fine dust in Seoul, and the correlation between the concentration of fine dust in Seoul and the concentration in each region was confirmed. In addition, predictions were made using the concentration of fine dust in each region and in Seoul. The lowest MAE (mean absolute error) in the prediction results was 12.13, which was about 15.17% better than the MAE of 14.3 presented in previous studies.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.3-12
• /
• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.