• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.63-74
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• 2007

Fast Fourier transform(FFT) is powerful, fast computation framework for convolution in many image restoration application. However, an actually observed image acquired with finite aperture of the acquisition device from the infinite background and it lost data outside the cropped region. Because of these the boundary artifacts are produced. This paper reviewed and summarized the up to date the techniques that have been applied to reduce of the boundary artifacts. Moreover, we propose a new block-based fast image restoration using combined extrapolation and edge-tapering without boundary artifacts with reduced computational loads. We apply edgetapering to the inner blocks because they contain outside information of boundary. And outer blocks use half-convolution extrapolation. For this process it is possible that fast image restoration without boundary artifacts.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.219-227
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• 2019

The educational method of physical computing, where students can experience software programming principles and practices while making concrete objects beyond outputs residing just inside of computer monitors, are drawing attentions. This current research sought an instructional method for pre-service teachers that they can experience 3D printing and modeling and at the same time they can understand programming principles in the 3D modeling processes. To achieve this aim, the TinkerCAD $Codeblocks^{(R)}$ was analyzed based on the computational thinking framework and a course utilizing the $Codeblocks^{(R)}$ to 3D modeling was devised. The designed class was applied to pre-service teachers and the students' perceptions of the class were collected by using a semi-structured survey. This study provides implications to software education for pre-service teachers as an instructional case that 3D printing is used to connecting computational thinking skills.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.315-320
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• 2020

Identity authentication is an important technology that has long been used in society to identify individuals and provide appropriate services. With the development of the Internet infrastructure, many areas have expanded into online areas, and identity authentication technologies have also expanded online. However, there is still a limit to identity authentication technology that relies entirely on trusted third parties like the government. A centralized identity management system makes the identification process between agencies with different identity management systems very complex, resulting in a waste of money and time for users. In particular, the limits of the centralized identity management system were clearly revealed in the face mask shortage in the 2020 COVID-19 crisis. A Decentralized Identity (DID) is a way for users to manage their identity on their own, and recently, a number of DID platform based on blockchain technology have been proposed. In this paper, we analyze the limitations of the existing centralized identity management system and propose a DID system that can be utilized in future national emergency situations such as COVID-19.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.307-317
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• 2019

This study is an example of the education of block coding and physical computing teaching tool for preservice teachers at the college of education. The students were familiar with coding and improved their coding skills in solving various problems through 'Entry' that support block coding. In addition, the students configured the computing system with various input / output devices of the physical computing teaching tool and controlled things through programming and produced the educational portfolio to experience the whole process of problem analysis, design, implementation, and testing in coding. We applied Flow based coding and Pair programming as the teaching methods, and the results of the survey to measure the effectiveness of the study show that students have a good understanding of the entry and physical computing teaching tool and using the combination of the entry and physical computing teaching tool were more effective in learning than the Entry-only coding. In addition, it was confirmed that the effect of Pair programming applied in the physical computing teaching tool.

• The KIPS Transactions:PartC
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• v.15C no.3
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• pp.149-156
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• 2008

JPEG2000 is the upcoming image coding standard that provides better compression rate and image quality compared with JPEG. Lazy-mode steganography guarantees the safe communication under the two information loss stages in JPEG2000. However, it causes the severe changes of the code-block noise variance sequence after embedding and that is detectable under the steganalysis using the Hilbert-Huang transform (HHT) based sequential analysis. In this paper, a JPEG2000 lazy-mode steganography method is presented. The code blocks which produce the sudden variation of the noise variance after embedding are estimated by calculating low precision code-block variance (LPV) and low precision code-block noise variance (LPNV). By avoiding those code-blocks from embedding, our algorithm preserves the sequence and makes stego images secure under the HHT-based steganalytic detection. In addition, it prevents a severe degradation of image quality by using JPEG2000 quality layer information. On various 2048 images, experiments are performed to show the effective reduction of the noise variation after message embedding and the stable performance against HHT-based steganalysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.18-27
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• 2009

In this paper, we propose a frame rate conversion algorithm using adaptive search-based motion estimation (ME). The proposed ME method uses recursive search, 3-step search, and single predicted search as candidates for search strategy. The best method among the three candidates is adaptively selected on a block basis according to the predicted motion type. The adaptation of the search method improves the accuracy of the estimated motion vectors while curbing the increase of computational load. To support the proposed ME method, an entire image is divided into three regions with different motion types. Experimental results show that the proposed FRC method achieves better image quality than existing algorithms in both subjective and objective measures.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11A
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• pp.936-944
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• 2003

In this paper, we propose an AND/XOR-based technology mapping method for field programmable gate arrays (FPGAs). Due to the fixed size of the programmable blocks in an FPGA, decomposing a circuit into sub-circuits with appropriate number of inputs can achieve excellent implementation efficiency. Specifically, the proposed technology mapping method is based on Davio expansion theorem to decompose a given Boolean circuit. The AND/XOR nature of the proposed method allows it to operate on XOR intensive circuits, such as error detecting/correcting, data encryption/decryption, and arithmetic circuits, efficiently. We conduct experiments using MCNC benchmark circuits. When using the proposed approach, the number of CLBs (configurable logic blocks) is reduced by 67.6% (compared to speed-optimized results) and 57.7% (compared to area-optimized results), total equivalent gate counts are reduced by 65.5 %, maximum combinational path delay is reduced by 56.7 %, and maximum net delay is reduced by 80.5 % compared to conventional methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.103-106
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• 2001

본 논문에서는 MPEG2비디오 스트림에서 직접 얻을 수 있는 정보들을 활용하여 카메라의 움직임을 추정하여 이를 기반으로 하여 움직이는 객체를 추정하고자 한다. 이를 위해, 먼저 MPEG2의 움직임 벡터는 압축의 효율성 때문에 움직임의 예측이 순서적이지 못한데, 예측 프레임들의 속성을 이용하여 이를 광 플로우(Optical Flow)를 갖는 움직임 벡터(Motion Vector)로 변환하였다. 그리고 이러한 벡터들을 이용하여 카메라의 기본적인 움직임인 팬(Fan), 틸트(Tilt). 줌(Zoom) 등을 정의하였다. 이를 위하여 팬, 틸트-줌 카메라 모델의 매개변수와 같은 의미의 $\Delta$x, $\Delta$y, $\alpha$값을 정의하고자 움직임 벡터 성분의 Hough변환을 이용하여 $\Delta$x, $\Delta$y, $\alpha$값들을 구하였다. 또한 이러한 카메라 움직임(Camera Operation)은 시간적으로 연속적으로 발생하는 특징을 이용하여 각 프레임마다 구한 카메라의 움직임을 보정하였다. 마지막으로 움직이는 객체의 추정은 우선 사용자가 원하는 객체를 바운딩박스 형태로 정의한 후 카메라 움직임이 보정된 객체의 움직임 벡터를 한 GOF(Group of Pictures) 단위로 면적 기여도에 따라 누적하여 객체를 추적하고 해석하였으며 DCT 질감 정보를 이용하여 객체의 영역을 재설정 하였다. 물론 압축된 MFEG2비디오에서 얻을 수 있는 정보들은 최대 블록 단위이므로 객체의 정의도 블록단위 이상의 객체로 제한하였다. 제안된 방법은 비디오 스트림에서 직접 정보를 얻음으로써 계산속도의 향상은 물론 카메라의 움직임특성과 움직이는 객체의 추적들을 활용하여 기존의 내용기반의 검색 및 분석에도 많이 응용될 수 있다. 이러한 개발 기술들은 압축된 데이터의 검색 및 분석에 유용하게 사용되리라고 기대되며 , 특히 검색 툴이나 비디오 편집 툴 또는 교통량 감시 시스템, 혹은 무인 감시시스템 등에서 압축된 영상의 저장과 빠른 분석을 요구시 필요하리라고 기대된다.