• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.189-191
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• 2005

In the scalable extension of H.264/AVC, the codec is based on a layered approach to enable spatial scalability. In each layer, the basic concepts of motion compensated prediction and intra prediction are employed as in standard H.264/AVC. Additionally inter-layer prediction algorithm between successive spatial layers is applied to remove redundancy. In the inter-layer prediction, as the prediction we can use the signal that is the upsampled signal of the lower resolution layer. In this case, coding efficiency can be variable as the kinds of interpolation filter. In this paper, we investigate the approach to select the interpolation filter for residual signal in order to optimal prediction.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• ETRI Journal
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• v.28 no.2
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• pp.145-154
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• 2006

In the decoding process associated with interframe wavelet coding, the inverse wavelet transform requires high computational complexity. However, as video technology starts to pervade all aspects of our lives, decoders are becoming required in various devices such as PDAs, notebooks, PCs, and set-top boxes. Therefore, a decoder's complexity needs to be adapted to the processor's computational power, and consequently a low-complexity codec is also required for scalable video coding. In this paper, we propose a method of controlling and lowering the complexity of the spatial wavelet transform while sustaining the same coding efficiency as that currently afforded. In addition, the proposed method may alleviate the ringing effect for slowly changing image sequences.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1803-1806
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• 2002

This paper describes an effective technique for lossless inter-frame video coding sequences based on a JPEG2000 CODEC. This technique has diminished the compression rate for lossless video coding. In this proposed method, firstly a predicted image for an in- put image is generated by motion estimation(ME), and then a difference image between the input image and the predicted image is calculated, and finally the difference image becomes an input image to a JPEG2000 encoder for lossless coding. Simulation results show the effectiveness of this method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.193-195
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• 2009

Bluetooth is a popluar wireless data transmission method with low power consumption. In this paper, we present a open source based player of video stream encoded by H.264 codec, which is transmitted via Bluetooth. An open source JM is used for H.264 decoding and modified for reading H.264 encoded data via Bluetooth. For display of decoded video data, SDL was utilized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2363-2369
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• 2014

The DVR system supports multiple cameras and should be able to receive images at 30 frames per channel in real time. Thus, The system is using Full-HD-grade Multiplexer and Hardware compression codec. In this paper, Describing the design and implementation for the 4-channel Full-HD-grade PC-based DVR using FPGA and GPU inside CPU without Multiplexer and Hardware codec. The existing DVR system for Full-HD-grade has drawbacks to acquire images of about only 20 frames per channel in real time. The system to acquire images of multiple channel in real time was designed using FPGA. The software for the system was implemented using Intel Media SDK. At the result of performance evaluation, It was satisfied all for the required conditions. The practicality of the system was confirmed as implementation the system without using hardware compression.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.10-14
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• 2015

Video Content owners seek to squeeze the maximum amount of revenue from their assets via distribution into more territories. Digital Cinema Package(DCP), trusted solution to distribute protected content to theaters, caters to relatively small user base, which limits revenue. With the growth of the Internet & other digital media, the economics of media content has changed dramatically. Security remains main concern to deliver content to millions of consumers using intelligent digital display devices like Tablets, Smartphones, Smart TVs, Desktop & Laptop. By making the video content available to this segment securely, content owners will benefit from increased revenue. Through this paper we propose Open Source HomeDCP model to distribute the content to home users for offline viewing. We propose to include other open source CODEC than JPEG2000/MPEG2, which are specifically designed for theatrical performance. Final image size will be further reduced considering the display device resolution where video will be finally played. Key Delivery Message(KDM) system to be altered to suit new devices. This will be a big boost to Content Economy as content owners would be able to distribute the content securely to the wider audience & ensure more revenue.

• ETRI Journal
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• v.44 no.1
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• pp.73-84
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• 2022

The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region-wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality.

• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.1017-1030
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• 2012

Most watermarking schemes for video contents protection have been studied to increase watermark's robustness and invisibility against such compressions and many kinds of signal processing after embedding copyright information to the original contents. This paper proposes an active watermarking that infect watermark to contents in the video decoding process using embedded infectious watermark and control signals from a video encoder side. To achieve this algorithm, we design a kernel based watermarking in video encoder side that is possible to recover the original contents and watermark in watermark detection procedure perfectly. And then, by reversible de-watermarking in video decoder side, we design the active watermark infection method using detected watermark and control signal. This means that our system can provide secure re-distributions of video contents without any quality degration and watermark bit error against transcoding or re-encoding processing. By experimental results, we confirmed that the embedded watermark was infected by video contents and codec perfectly without any declines of compression ratio and video quality.