• ETRI Journal
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• 제25권3호
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• pp.179-186
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• 2003

Using biometrics to verify a person's identity has several advantages over the present practices of personal identification numbers (PINs) and passwords. At the same time, improvements in VLSI technology have recently led to the introduction of smart cards with 32-bit RISC processors. To gain maximum security in verification systems using biometrics, verification as well as storage of the biometric pattern must be done in the smart card. However, because of the limited resources (processing power and memory space) of the smart card, integrating biometrics into it is still an open challenge. In this paper, we propose a fingerprint verification algorithm using a multi-resolution accumulator array that can be executed in restricted environments such as the smart card. We first evaluate both the number of instructions executed and the memory requirement for each step of a typical fingerprint verification algorithm. We then develop a memory-efficient algorithm for the most memory-consuming step (alignment) using a multi-resolution accumulator array. Our experimental results show that the proposed algorithm can reduce the required memory space by a factor of 40 and can be executed in real time in resource-constrained environments without significantly degrading accuracy.

• 방송공학회논문지
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• 제2권2호
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• pp.216-224
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• 1997

본 논문에서는 중간 영상 합성을 위한 거리 정보 추출에 관한 방법을 제안한다. 거리 정보의 추출을 위한 스테레오 정합 방법 중 여러 대의 카메라를 사용함으로써 정합의 정확도를 높인 MBS(Multiple-Baseline Stereo) 방법이 있다. 그러나 MBS 방법은 정합창을 고려함으로써 깊이맵의 경계선 연장(boundary overreach) 문제를 가져왔고 또한 폐색 영역에 대한 적절한 처리 방법을 제시하지 않고 있다. 또한 정확도를 높이기 위하여 처리 시간의 증가를 가져왔다. 본 논문에서는 정합창을 사용함으로써 발생하는 깊이맵의 경계선 연장 문제를 해결하며 처리시간을 줄일 수 있는 방법론으로서 계층적 방법인 MR-MBS (Multi-Resolution MBS) 방법을 제시한다. 또한 폐색 영역에 대한 처리 방법으로 카메라 배치를 고려한 적응적 폐색 영역 처리 방법을 제안한다.

• 전기전자학회논문지
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• 제24권1호
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• pp.186-193
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• 2020

본 논문에서는 Zynq SoC 환경에서 재구성 가능한 하드웨어 가속기를 지원하는 멀티쓰레딩 시스템을 제안한다. 압축된 정지 영상의 픽셀 데이터를 복원하는 고성능 JPEG 디코더를 구현하고 2D-IDCT 함수를 재구성 가능한 하드웨어 가속기로 설계하여 성능을 검증한다. 구현된 시스템에서 최대 4개의 재구성 가능한 하드웨어 가속기는 소프트웨어 쓰레드와 동기화되어 연산을 수행할 수 있으며 이미지 해상도와 압축률에 따라 다른 성능 향상을 보인다. 1080p 해상도 영상의 경우 17:1의 압축률에서 최대 79.11배의 성능 향상과 99fps의 throughput 속도를 보여준다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.927-930
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• 2004

동물의 눈이 효율적인 시각 정보 수집을 위해 사용하는 선택적 주의 방법을 기본으로 하여, 여기에 다중 해상도 방법을 적용하여 좀 더 동물의 눈과 비슷한 선택적 주의 방법을 제안하였으며 이를 이용한 실험 결과를 통해 다중 해상도 기법의 유용성을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.

• 천문학회지
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• 제47권2호
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• pp.43-47
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• 2014

Many advanced ground-based solar telescopes improve the spatial resolution of observation images using an adaptive optics (AO) system. As any AO correction remains only partial, it is necessary to use post-processing image reconstruction techniques such as speckle masking or shift-and-add (SAA) to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. In the New Vacuum Solar Telescope (NVST), the spatial resolution in solar images is improved by frame selection and SAA. In order to overcome the burden of massive speckle data processing, we investigate the possibility of using the speckle reconstruction program in a real-time application at the telescope site. The code has been written in the C programming language and optimized for parallel processing in a multi-processor environment. We analyze the scalability of the code to identify possible bottlenecks, and we conclude that the presented code is capable of being run in real-time reconstruction applications at NVST and future large aperture solar telescopes if care is taken that the multi-processor environment has low latencies between the computation nodes.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.794-802
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• 2022

The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.25³ on the NYUv2 dataset.

• ETRI Journal
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• 제38권6호
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• pp.1207-1217
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• 2016

The general method of machine learning has encountered disadvantages in terms of the significant amount of time and effort required for feature extraction and engineering in natural language processing. However, in recent years, these disadvantages have been solved using deep learning. In this paper, we propose a mention pair (MP) model using deep learning, and a system that combines both rule-based and deep learning-based systems using a guided MP as a coreference resolution, which is an information extraction technique. Our experiment results confirm that the proposed deep-learning based coreference resolution system achieves a better level of performance than rule- and statistics-based systems applied separately

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.401-404
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• 2004

SAR (Synthetic Aperture Radar) signal data need a focusing procedure to make the information available to the user. In recent SAR systems, various sensing modes and mission operations are applied to acquire high-resolution SAR images. Therefore, in order to develop generalized focusing software for multi-satellites, a regularized parameter configuration that sufficiently represents sensor and platform characteristics of the SAR system is required. The objective of this paper is to introduce the consideration of parameter definition for developing a generalized SAR processor and to discuss the flexibility and extensibility of defined parameters. The proposed parameter configuration can be applied to a SAR processor. Experiments based on real data will show the suitability of the suggested processing parameters.