• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.117-126
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• 2012

This paper provides a method for compression transmission of on-chip bus data. As the data traffic on on-chip buses is rapidly increasing with enlarged video resolutions, many video processor chips suffer from a lack of bus bandwidth and their IP cores have to wait for a longer time to get a bus grant. In multimedia data such as images and video, the adjacent data signals very often have little or no difference between them. Taking advantage of this point, this paper develops a simple bus data compression method to improve the chip performance and presents its hardware implementation. The method is applied to a Video Codec - 1 (VC-1) decoder chip and reduces the processing time of one macro-block by 13.6% and 10.3% for SD and HD videos, respectively

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.107-116
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• 1998

Video data are retrieved and stored in various compressed forms according to their characteristics. In this paper, we present a generic data model that captures the structure of a video document and that provides a means for indexing a video stream. Using this model, we design and implement CVIMS (the MPEG-2 Compressed Video Information Management System) to store and retrieve video documents. CVIMS extracts I-frames from MPEG-2 TS files, selects key-frames from the I-frames, and stores in database the index information such as thumbnails, captions, and picture descriptors of the key-frames. And, CVIMS retrieves MPEG-2 video data using the thumbnails of key-frames and various labels of queries. And also, the system is accessible by a web interface.

• Journal of Korean Association for Spatial Structures
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• v.19 no.4
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• pp.103-110
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• 2019

The cable-based retractable membrane roof makes it impossible to maintain its shape and stiffness during driving process, unlike the hard-type retractable roof. Consequently, monitoring using a relatively simple wireless video transmission device is required. However, since video data has a bigger transmission rating than other monitoring data in terms of the structure velocity or acceleration, there is a need to develop transmission device that is easy to install and entails low maintenance cost. This paper studies on a real-time video transmission system for monitoring the cable-based retractable membrane roof while driving. A video transfer software, using the mobile network, is designed and the embedded system is constructed. Ultimately, the data transmission server is tested. Connecting a trolley to the system allows testing of the validity and efficiency of the developed system through the video data transmitted in the driving process. Result of the test shows that the developed system enables multi-device data transfer with monitoring via the mobile network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2328-2340
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• 1996

Until now, the transmission of data for VOD(Video on Demenad) was based on a real time modelling of video data. Markow Modulated Fluid Sources(MMFS) and Markow Modulated Poisson Sources(MMPS) are the most widely used modelling methods. But the charactersitics of the VBR(Variable Bit Rate) signal prevents modelling from actually being "real-time". Also these methods call for the use of large buffers for the abolishment of cell loss. These modelling methods are, of course, useful i case of teleconferences where a real time modelling of video traffic is inevitable, but they are insufficient in cases where the characteristic infomation of video traffic can be obtained beforehand-cases such as VOD. Video data is speial in that if one file is preprocessed all other products can simply be copied from that onepreprocessed file. This characteristic helps reduce the overhead arising from the job of drawing out characteristic information to almost zero. But still, compared to the existing real time modelling method data transmission using characteristic information succeeds in raising the efficiency of data transmission. In tis paper we will outline a method of dta transmission which use the characteristic information of each video stream, and evaluate this method through some experiments.periments.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.183-190
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• 2005

In this thesis, first, we propose I-frame encryption techniques of video data for video data itself encryption and propose license agent that processing user's certification and decryption in client system automatically when user execute encrypted video data in system server. License agent runs user's certification, encryption and decryption of video data based on PID(Public Key Infrastructure) using shared key-pool when execute of video data. Also, compose duplex buffer control and propose real time decryption method using efficient buffer scheduling to reduce much playing delay times that happen processing decryption when execute of videoa data of high-capacity.

• Proceedings of the KSRS Conference
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• v.2
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• pp.791-793
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• 2006

In the satellite camera, the incoming light source is converted to electronic analog signals by the electronic component for example CCD (Charge Coupled Device) detectors. The analog signals are amplified, biased and converted into digital signals (pixel data stream) in the video processor (A/Ds). The outputs of the A/Ds are digitally multiplexed and driven out using differential line drivers (two pairs of wires) for cross strap requirement. The MSC (Multi-Spectral Camera) in the KOMPSAT-2 which is a LEO spacecraft will be used to generate observation imagery data in two main channels. The MSC is to obtain data for high-resolution images by converting incoming light from the earth into digital stream of pixel data. The video data outputs are then MUXd, converted to 8 bit bytes, serialized and transmitted to the NUC (Non-Uniformity Correction) module by the Hotlink data transmitter. In this paper, the video data streams, the video data format, and the image data processing routine for satellite camera are described in terms of satellite camera control hardware. The advanced satellite with very high resolution requires faster and more complex image data chain than this algorithm. So, the effective change of the used image data chain and the fast video data transmission method are discussed in this paper

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.687-694
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• 2003

According to the rapid increase of multimedia data quantity recently, various means of video data search has been desired. In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.638-642
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• 2002

User in video data utilization of high-capacity can grasp whole video data at a look. Offer frame list that summarize information of video data to do so that can remake video from branch that want when need. Need index process of video data for effective video retrieval. This treatise wishes to propose effective method about scene change point detection of video that is been based on contents base index. Proposed method video data so that can grasp whole structure of video detection color value of schedule pixel for diagonal line direction in image sampling do. Data that get into sampling could grasp scene change point on one eye. Color value of pixel that detection in each frame is i frame number by i$\times$j procession to procession A, j stores to reflex height of frame. Introduce MSE and calculate mean error of each frame. If exceed mean error and schedule critical value, wish to detect the frame for scene change point.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.451-456
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• 2018

UAVs (Unmanned Aerial Vehicles) are widely used for maintenance and monitoring of facilities. It is necessary to acquire a high-resolution image for evaluating the appearance state of the facility in safety inspection. In addition, it is essential to acquire the video data in order to acquire data over a wide area rapidly. In general, since video data does not include position information, it is difficult to analyze the actual size of the inspection object quantitatively. In this study, we evaluated the utilization of 3D point cloud data of bridges using a matching between video frames and reference photos. The drones were used to acquire video and photographs. And exterior orientations of the video frames were generated through feature point matching with reference photos. Experimental results showed that the accuracy of the video frame data is similar to that of the reference photos. Furthermore, the point cloud data generated by using video frames represented the shape and size of bridges with usable accuracy. If the stability of the product is verified through the matching test of various conditions in the future, it is expected that the video-based facility modeling and inspection will be effectively conducted.