• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1370-1378
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• 1996

A subjective video quality assessment methods are proposed based on CCIR Rec. 500-5 for an evaluation and testing of compressed video quality and performance of video codec to be designed in accordance with the MPEG-2 MP ML specification which is adapted as a DTV standard for Korea digital DBS. Video sequence compressed in compliance with MPEG-2 MP ML encoding parameterswastested by the proposed video quality evaluation procedure. Test sequence were compressed at the bit rate 6Mbps, 7.5Mbps and 9Mbps, repectively. Test results of the 7.5Mbps bitrate showed a satisfactory picture quality at about 4.0 on the 5.0 absolute scale of ITU-R 500-5.

• Journal of the Semiconductor & Display Technology
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• v.16 no.1
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• pp.75-80
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• 2017

Nowadays, smart phone is being popularly used for communication, entertainment, and information retrieval. While demands on video traffic over mobile networks increases sharply, the wireless link capacity is often limited to fully support the traffic demand. Therefore, the size of video data needs to be reduced to provide high quality video with limited capacity. To handle this issue, we propose a video editing system using the ffmpeg library. The proposed system can provide a high quality video with a relatively small data size, thereby facilitating the mobile streaming services and live-video games.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.11-17
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• 2010

In this paper, we propose efficient rate control algorithm for video near-lossless compression. The proposed method adjusts pixel error range using amounts of previous encoded bits and target bits at a slice encoding interval. Thus, encoded bits by the proposed method are transmitted well through limited bandwidth without overflow. Also, target bits and encoded bits can be controlled according to transmission policy. Experimental results show that our proposed method not only almost fits compression ratio, but also has better image quality.

• ETRI Journal
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• v.38 no.5
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• pp.868-878
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• 2016

A multi-screen environment provides a new opportunity for digital signage applications, where various irregularly shaped screens are employed as an effective means for advertisements and information. A formation method applicable to numerous irregularly shaped screens is proposed to provide a new perspective on digital signage applications. The crucial part of the proposed method comes from the geometric sensing of each screen and the formation of a virtual screen where geometrically aligned content extraction and encoding are employed for content transmission to each screen. In addition, a software-based synchronization method for the proposed system is proposed to address the frame-level synchronization between screens. The experimental results of the proposed method show an improved performance of the frame-level synchronization, where the inconsistency between frames is not identified.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.169-180
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• 2019

Transmitting visual information over a broadcasting network is not only prone to a copyright violation but also is a forgery. Authenticating such information and protecting its authorship rights call for more advanced data encoding. To this end, electronic watermarking is often adopted to embed inscriptive signature in imaging data. Most existing watermarking methods while focusing on robustness against degradation remain lacking of measurement against security loophole in which the encrypting scheme once discovered may be recreated by an unauthorized party. This could reveal the underlying signature which may potentially be replaced or forged. This paper therefore proposes a novel digital watermarking scheme in temporal-frequency domain. Unlike other typical wavelet based watermarking, the proposed scheme employed the Lorenz chaotic map to specify embedding positions. Effectively making this is not only a formidable method to decrypt but also a stronger will against deterministic attacks. Simulation report herein highlights its strength to withstand spatial and frequent adulterations, e.g., lossy compression, filtering, zooming and noise.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.117-125
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• 2014

In this paper, a novel hardware architecture of the LT codec is presented where non-BP based decoding algorithm is applied. Novel LT codec architecture is designed with an efficient degree distribution unit using Verilog HDL. To perform permutation operation, different initial valued or time shifted counters have been used to get pretty well permutations and an effect of randomness. The codec will take 128 bits as input and produce 256 encoded output bits. The simulation results show expected performances as the implemented distribution and the original distribution are pretty same. The proposed LT codec takes 257.5 cycle counts and $2.575{\mu}s$ for encoding and decoding instead of 5,204,861 minimum cycle counts and 4.43s of the design mentioned in the previous works where iterative soft BP decoding was used in ASIC and ASIP implementation of the LT codec.

• Journal of the Korean Physical Society
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• v.73 no.12
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• pp.1908-1917
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• 2018

The binding affinity between the T-cell receptors (TCRs) and antigenic peptides mainly determines immunological recognition. It is not a trivial task that T cells identify the digital sequences of peptide amino acids by simply relying on the integrated binding affinity between TCRs and antigenic peptides. To address this problem, we examine whether the affinity-based discrimination of peptide sequences is learnable and generalizable by artificial neural networks (ANNs) that process the digital experimental amino acid sequence information of receptors and peptides. A pair of TCR and peptide sequences correspond to the input for ANNs, while the success or failure of the immunological recognition correspond to the output. The output is obtained by both theoretical model and experimental data. In either case, we confirmed that ANNs could learn the immunological recognition. We also found that a homogenized encoding of amino acid sequence was more effective for the supervised learning task.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.156-162
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• 2022

Image compression plays an important role in encoding and improving various forms of images in the digital era. Recent researches have focused on the principle of deep learning as one of the most exciting machine learning methods to show that it is good scheme to analyze, classify and compress images. Various neural networks are able to adapt for image compressions, such as deep neural networks, artificial neural networks, recurrent neural networks and convolution neural networks. In this review paper, we discussed how to apply the rule of deep learning to obtain better image compression with high accuracy, low loss-ness and high visibility of the image. For those results in performance, deep learning methods are required on justified manner with distinct analysis.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.129-133
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• 2023

Image compression is a fundamental technique in the field of digital image processing, which will help to decrease the storage space and to transmit the files efficiently. Recently many deep learning techniques have been proposed to promise results on image compression field. Since many image compression techniques have artifact problems, this paper has compared two deep learning approaches to verify their performance experimentally to solve the problems. One of the approaches is a deep autoencoder technique, and another is a deep convolutional neural network (CNN). For those results in the performance of peak signal-to-noise and root mean square error, this paper shows that deep autoencoder method has more advantages than deep CNN approach.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.185-191
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• 2012

This study deals with the technical approach related to the protection of digital video contents copyright, which has currently become a major issue in the digital contents market. With the production and distribution of digital video contents rapidly increasing, various policies and technical approaches are being made in relation to the protection of intellectual property rights. The technical approach from a DRM (Digital Rights Management) perspective was made from various angles, but its limitations have also been exposed in terms of convenience and quality. In this study, rather than the existing encoding certification and watermark technologies, it introduces technical approaches from a content-based copy detection method, while suggesting a copy detection method using the representative color sequence. In particular, this study takes into consideration the distribution environment of the domestic video market and deals with the technical approach in a direction that can control the illegal distribution of high quality videos.