• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.511-516
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• 2006

In this raper, we propose the Sequentiel Couleur Avec Memoire or Sequential Color with Memory (SECAM) video encoder system using modified anti-cloche filters and the SECAM video decoder system using a band pass filter (BPF) and an error-free square root. The SECAM encoder requires an anti-cloche filter recommended by International Telecommunication Union-Recommendation (ITU-R) Broadcasting service Television (BT) 470. However, the design of the anti-cloche filter is difficult because the frequency response of the anti-cloche filter is very sharp around rejection-frequency area. So, we convert the filter into a hish pass filter (HPF) by shifting the rejection frequency of 4.286MHz to 0Hz frequency. The design of HPF becomes very easy, compared to that of the anti-cloche filter. The proposed decoder also uses an error-free square root, two differentiators and trigonometric functions to extract color-component information of Db and Dr accurately from frequency modulation (FM) signals in SECAM systems. Also, the BPF in decoder it used for removing color noise in chrominance and dividing CVBS into chrominance and luminance. The proposed systems are experimentally demonstrated with Altera FPGA APEX20KE EP20K1000EBC652-3 device and TV sets.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.542-553
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• 2006

Because Y and C signals in a composite video signal are piled one on another in the same frequency, it is impossible to separate them completely. Therefore, it is necessary to develop efficient separation technique in order to minimize degradation of video quality. In this paper, we propose wavelet-based 3D comb filter algorithm and architecture for separating Y and C signals from a composite video signal. The proposed algorithm uses wavelet transform and thresholding of compared lines for acquiring the maximum video quality. Simulation results show that the proposed algorithm has better image quality and better PSNR than previous algorithms. For real application of the proposed algorithm, we developed a hardware architecture and the architecture was implemented by using VHDL. Finally, a VLSI layout of the proposed architecture was generated by using 0.25 micrometer CMOS process.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.211-214
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• 2003

Current VOD embodiment way is embodied using PC base. However, achieved research that embody this by Embedded System that PC base is not. OS of this system used WindowsCE.net and x86core used having built-ined SC1200(National company's Geode's familys) by CPU and memory used 128MByte SDRAM. Used Mpeg Decoder for processing of video data, and used Enthernet Controller for Internet. Composite, component, S-Video of video output section of this system is and select one of these and connect on TV and did so that get into action. Actuality implementation manufactured necessary BIOS, WinodwsCE.NET Porting, DeviceDriver in system development and necessary simple Application in action confirmation, and Video Player used Window Media Player had included to WindowsCE.net. Therefore, treatise that see to supplement shortcomings of VOD service been embodying in current PC in Embedded System's form embody that there is sense do can.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.138-144
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• 2018

A video is a vivid medium similar to human's visual-linguistic experiences, since it can inculcate a sequence of situations, actions or dialogues that can be told as a story. In this study, we propose story learning/regeneration frameworks from videos with successive event order supervision for contextual coherence. The supervision induces each episode to have a form of trajectory in the latent space, which constructs a composite representation of ordering and semantics. In this study, we incorporated the use of kids videos as a training data. Some of the advantages associated with the kids videos include omnibus style, simple/explicit storyline in short, chronological narrative order, and relatively limited number of characters and spatial environments. We build the encoder-decoder structure with successive event order embedding, and train bi-directional LSTMs as sequence models considering multi-step sequence prediction. Using a series of approximately 200 episodes of kids videos named 'Pororo the Little Penguin', we give empirical results for story regeneration tasks and SEOE. In addition, each episode shows a trajectory-like shape on the latent space of the model, which gives the geometric information for the sequence models.