• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.40-42
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• 2012

Colorization is a method using computer to add color to a black and white image automatically. The input is a grayscale image and some representative pixels (RPs). The RPs contain the color information for the image, and it indicates each region's color information. Colorization-based coding is a novel way for lossy image compression, it decodes a color image to get grayscale image and extracts RPs from the image. Because RPs decides the region's color and we also want small data size for image compression, form this viewpoint the paper proposes a way to get better and fewer RPs based on watershed segmentation. According to the segmentation result we also improve the original chrominance blending colorization method to save decode time and get better reconstruct image.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.192-194
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• 2005

Acceptance of the international standards for video compression, such as H.261, MPEG-1 and MPEG-2, along with the developments in video codec hardware, has created an explosion of application. Among these, the long time quest for long-distance digital video transmission causes an increasing interest in transporting compressed video over networks which are nontraditional for this purpose, including asynchronous transfer mode networks, the Internet, and cellular and wireless channels. Transmission of compression video over packet network is improved for error resilience. And layered video coding techniques improves error resilience. We present a efficient method of scalable video coding for low bandwidth.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.1
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• pp.81-87
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• 1988

This paper proposes a new EBTC(extended block truncation coding) algorithm extended from the BTC for image compression. The EBTC has a capability to eliminate the defects of BTC, such as the deterioration of resolution or blocky effect,and to make a real-time processing like BTC. It shows better performances than the DPCM and the transform coding. Especially, it is a suitable coding method for the high quality picture transmission. It may be adequate to the system of transmission rate of 30-50 Mbits/sec. The picture quality has been scarecely degraded with a vector quantization to the EBTC output at the bit rate of 1.25 bits/pel. The bit rate of the scalar quantized EBTC method is 2.6-3.7 bits/pel.

• Bulletin of the Society of Naval Architects of Korea
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• v.21 no.2
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• pp.19-27
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• 1984

An extension of the finite element method to the stability analysis of shells of revolution under static axisymmetric loading is presented in this paper. A systematic procedure for the formulation of the problem is based upon the principle of virtual work. This procedure results in an eigenvalue problem. For solution, the shell of revolution is discretized into a series of conical frusta. The buckling mode in the circumferential direction is assumed, this assumption makes the problem economical for the computing time. The present method is applied to a number of shells of revolution, under axial compression or lateral pressure, and comparision are made with other theoretical results. The results show good agreement each other. The effects of aspect ratio, boundary conditions and buckling modes on the buckling strength of shells of revolution are studied. Also the optimum shape of cylindrical shell under uniform axial compression is obtained from the view point of structural stability.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.205-214
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• 2020

With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1817-1823
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• 1998

V.42bis, a type of LZW(Lempel-Ziv-Welch) code, is well-known as theinter national standard is asynchronous data compression. In this paper, we analyze several undesirable phenomena arising from the application of v.42bis to high speed data transmission, and we propose a modified technique to overcome them. the proposed technique determines the proper size of the dictionary, one of important factors affecting the compression ratio, and improves the method of dictionary generation for a higher compression ratio. Furthermore, we analyze the problem of excessive mode changes and solve it to a certain degree by adjusting the threshold for mode change. By doing this, we can achieve smiller variation of the compression ratio in time. This improvement chtributes to easier and better design and control of the buffer in high speed data transmission.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.41-47
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• 2002

Fractal image compression can reduce the size of image data by the contractive mapping that is affine transformation to find the block(called as range block) which is the most similar to the original image. Even though fractal image compression is regarded as an efficient way to reduce the data size, it has high distortion rate and requires long encoding time. In this paper, we presented a hybrid fractal image compression system with the modified SOFM Vector Quantizer which uses improved competitive learning method. The simulation results showed that the VQ hybrid fractal using improved competitive loaming SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.53-62
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• 2021

Deep learning models such as convolutional neural networks and recurrent neual networks process a huge amounts of data, so they require a lot of storage and consume a lot of time and power due to memory access. Recently, research is being conducted to reduce memory usage and access by compressing data using the feature that many of deep learning data are highly sparse and localized. In this paper, we propose a compression-decompression method of storing only the non-zero data and the location information of the non-zero data excluding zero data. In order to make the location information of non-zero data, the matrix data is divided into sections uniformly. And whether there is non-zero data in the corresponding section is indicated. In this case, section division is not executed only once, but repeatedly executed, and location information is stored in each step. Therefore, it can be properly compressed according to the ratio and distribution of zero data. In addition, we propose a hardware structure that enables compression and decompression without complex operations. It was designed and verified with Verilog, and it was confirmed that it can be used in hardware deep learning accelerators.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.221-224
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• 2005

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.499-502
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• 2001

Fractal image coding suffers from the long search time of domain pool although it provides many properties including the high compression ratio. We find that the normalized variance of a block is independent of contrast, brightness. Using this observation, we introduce a self similar block searching method employing the d-dimensional nearest neighbor searching. This method takes Ο(log/N) time for searching the self similar domain blocks for each range block where N is the number of domain blocks. PSNR (Peak Signal Noise Ratio) of this method is similar to that of the full search method that requires Ο(N) time for each range block. Moreover, the image quality of this method is independent of the number of edges in the image.