• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.921-924
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• 2013

최근 무선랜 기반 실내 측위시스템을 활용하는 위치정보 서비스가 주목을 받고 있다. 기존 측위 방식에서는 주로 삼각측량 기법에 의존하여 사용자 단말의 위치를 측정하고 있으나, 실내 벽 등의 장애물로 인하여 정확한 측위가 어려울 뿐만 아니라 측위 오차가 크다는 문제점이 있다. 본 논문에서는 무선랜 기반 실내 측위시스템에서 방(room) 등의 블록(block) 단위로 사용자의 위치를 측정하는 방법을 제시한다. 실험 결과, 제안 방식은 기존 방식에 비해 측위 오차를 50% 이상 감소시킬 수 있음을 확인하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.3-9
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• 2009

In this paper we introduce a new side-channel attack using block cipher cryptanalysis named meet-in-the middle attack. Using our new side-channel technique we introduce side-channel attacks on AES with reduced masked rounds. That is, we show that AES with reduced 10 masked rounds is vulnerable to side channel attacks based on an existing 4-round function. This shows that one has to mask the entire rounds of the 12-round 192-bit key AES to prevent our attacks. Our results are the first ones to analyze AES with reduced 10 masked rounds.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.401-410
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• 2023

In this paper, we propose optimization methods for implementing SPARKLE, one of the NIST LWC finalists, on a 64-bit ARMv8 processor. The proposed methods consist of two approaches: an implementation using ARM A64 instructions and another using NEON ASIMD instructions. The A64-based implementation is optimized by performing register scheduling to efficiently utilize the available registers on the ARMv8 architecture. By utilizing the optimized A64-based implementation, we can achieve speeds that are 1.69 to 1.81 times faster than the C reference implementation on a Raspberry Pi 4B. The ASIMD-based implementation, on the other hand, optimizes data by parallelizing the ARX-boxes to perform more than three of them concurrently through a single vector instruction. While the general speed of the optimized ASIMD-based implementation is lower than that of the A64-based implementation, it only slows down by 1.2 times compared to the 2.1 times slowdown observed in the A64-based implementation as the block size increases from SPARKLE256 to SPARKLE512. This is an advantage of the ASIMD-based implementation. Therefore, the ASIMD-based implementation is more efficient for SPARKLE variant block cipher or permutation designs with larger block sizes than the original SPARKLE, making it a useful resource.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.265-270
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• 2011

In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.981-991
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• 2011

MIP(Maximum Intensity Projection) is a volume rendering technique which is essential for the medical imaging system. MIP rendering based on the ray casting method produces high quality images but takes a long time. Our aim is improvement of the rendering speed using GPGPU(General-purpose computing on Graphic Process Unit) technique. In this paper, we present the ray casting algorithm based on CUDA(an acronym for Compute Unified Device Architecture) which is a programming language for GPGPU and we suggest new acceleration methods for CUDA. In detail, we propose the block based space leaping which skips unnecessary regions of volume data for CUDA, the bisection method which is a fast method to find a block edge, and the initial value estimation method which improves the probability of space leaping. Due to the proposed methods, we noticeably improve the rendering speed without image quality degradation.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.561-571
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• 2019

Programming education generally includes problem analysis process, automation through algorithms and programming, and generalization process. It is a good software education method for students in improving computing thinking. However, it was found that beginners had difficulties in understanding instruction usage, writing algorithms, and implementing programming. In this study, we developed a game programming education model and curriculum for programming education of pre-service teachers. The 4E model consisted of empathy, exploration, engagement and evaluation. In addition, it is configured to learn game core elements and core command blocks by each stage. To help the pre-service teachers understand the use of various programming blocks, a three-step teaching and learning method was presented, consisting of example learning, self-game creation, and team-based projects. As a result of applying and verifying the curriculum for 15 weeks, it showed significant results in the 4E model and pre-service teachers' perception of block programming competence and the level of computational thinking on the submitted game project results was also high.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.204-211
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• 2020

In this paper, we propose an optimal deep learning network architecture for main object location detection through weak supervised learning. The proposed network adds convolution blocks for improving the localization accuracy of the main object through weakly-supervised learning. The additional deep learning network consists of five additional blocks that add a composite product layer based on VGG-16. And the proposed network was trained by the method of weakly-supervised learning that does not require real location information for objects. In addition, Grad-CAM to compensate for the weakness of GAP in CAM, which is one of weak supervised learning methods, was used. The proposed network was tested through the CUB-200-2011 data set, we could obtain 50.13% in top-1 localization error. Also, the proposed network shows higher accuracy in detecting the main object than the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.996-1003
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• 2022

In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

• The KIPS Transactions:PartB
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• v.8B no.3
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• pp.311-318
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• 2001

본 논문에서는 중첩되는 영상사이의 평면 투영 변환을 구하는 방법을 제안하였다. 제안한 방법은 정규상관과 직사각형-사변형 평면 투영 변환에 기반 한다. 블록 정합을 이용하여 전역 이동을 계산하고, 중첩되는 영역의 정규 상관 계수 값을 최대로 하는 4개의 대응점을 찾기 위하여 가우시안 영상 피라미드에서 SA(simulated annealing) 알고리즘을 사용하였다. 이들 대응점에서 직사각형-사변형으로의 사상을 이용하여 평면 투영 변환을 계산하고, 마지막으로 중첩되는 영역의 RGB 컬러 값을 선형 가중치에 의해 혼합하였다. 실험으로 세 장의 영상을 한 장읠 큰 모자익 영상으로 합성하는 결과를 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.967-969
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• 2013

In this paper, we propose an efficient mult-signature scheme based on a bilinear mapping for shared data in the cloud and prove the security of the proposed scheme using the difficulty of the computational Diffie-Hellman problem. For verification, the scheme is using the sum of the hash values of stored data rather than the entire data, which makes it feasible to reduce the size of the downloaded data.