• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.421-425
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• 2012

The objective of this study was to improve the detection limit of rapid detection kit for Salmonella Typhimurium by image analysis system. The rapid detection kit was comprised of four elements: sample pad, conjugate pad, nitrocellulose pad and absorbent pad. Gold nanoparticle and Salmonella antibody were used as a tag and a receptor. Salmonella antibody and goat rabbit IgG antibody were used as test and control lines on nitrocellulose membrane. The color intensity of test line began to increase from $10^5CFU/mL$ of Salmonella sample. A multiple linear regression analysis was employed to explain the relationship between predicted and measured number of Salmonella cells. The developed model could successfully predict the cell number of Salmonella with validation against extra-experimental result.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.75-82
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• 2008

In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the performance of the first detected symbol which causes error propagation, the proposed algorithm achieves a considerable performance gain as compared to the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In case of 16QAM MIMO-SM system with 4 transmit and 4 receive ($4{\times}4$) antennas, at $BER=10^{-3}$ the proposed algorithm obtains the gai improvement of about 2.5-13.5 dB over the conventional algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.521-532
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• 2015

This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7C
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• pp.616-626
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• 2007

In spatially multiplexed MIMO systems that enable high data rate transmission over wireless communication channels, the spatial demultiplexing at the receiver is a challenging task, and various demultiplexing methods have been developed recently by many researchers. Among the previous methods, maximum likelihood detection with QR decomposition and M-algorithm (QRM-MM)), and sphere decoding (SD) schemes have been reported to achieve a (near) maximum likelihood (ML) performance. In this paper, we propose a novel signal detection method that achieves a near ML performance in a computationally efficient manner. The proposed method is demonstrated via a set of computer simulations that the proposed method achieves a near ML performance while requiring a complexity that is comparable to that of the conventional MMSE-OSIC. We also show that the log likelihood ratio (LLR) values for all bits are obtained without additional calculation but as byproduct in the proposed detection method, while in the previous QRM-MLD, SD, additional computation is necessary after the hard decision for LLR calculation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1263-1268
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• 2018

In this paper, a video analysis is proposed to implement video surveillance system with deep learning object detection and probabilistic data association filter for tracking multiple objects, and suggests its implementation using GPU. The proposed video analysis technique involves object detection and object tracking sequentially. The deep learning network architecture uses ResNet for object detection and applies probabilistic data association filter for multiple objects tracking. The proposed video analysis technique can be used to detect intruders illegally trespassing any restricted area or to count the number of people entering a specified area. As a results of simulations and experiments, 48 channels of videos can be analyzed at a speed of about 27 fps and real-time video analysis is possible through RTSP protocol.

• Journal of Aerospace System Engineering
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• v.17 no.6
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• pp.100-107
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• 2023

Open-phase fault in a Permanent Magnet Synchronous Motor (PMSM) occurs due to disconnection of phases of motor windings or inverter switch failures. When an open-phase occurs, it leads to the generation of torque ripples and vibrations in the motor, which can have a critical impact on the safety of the vehicle (including aircraft) using a PMSM as an actuator. Therefore, rapid fault detection and classification are essential. This paper proposes a classification method for detecting open-phase faults and locating fault positions in a PMSM used in aircraft applications. The proposed approach uses an Extended Kalman Filter for fault diagnosis, and it subsequently classifies faults using a Multiple Model filter.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.409-412
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• 2011

본 논문에서는 흉부 X선 영상으로부터 폐 종류 음영을 검출하기 위한 필터를 예측해서 바람직하게 평가하기 위한 방법을 제안한다. 더욱이 그 평가방법을 이용해서 이전부터 제안한 다중해상도 라플라시안-가우시안 필터의 평가를 행한다. 전문의의 진단보조 혹은 종합자동진단시스템의 구성요소로서 필터가 행하는 역할을 고려한 후에 필터가 만족해야할 조건 및 그 조건을 만족한 경우에 있어서 몇가지 성능평가 척도를 명확히 한다. 제안한 평가방법을 통해서 다중해상도 필터가 단일해상도 필터에 비해 높은 성능을 갖게됨을 명확히 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.807-809
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• 2004

본 논문에서는 광 부호분할다중접속(OCDMA) 시스템 구현을 위해 각 가입자의 시간ㆍ파장영역의 2차원 부호할당 및 변경이 가능하고 다중 사용자의 암호화된 데이터의 동시 전송과 모든 수신 노드에서 복원이 가능한 OCDMA 시스템 구조를 제안하였다. 또한 기존의 이중 광 하드리미터를 제한증폭기와 AND 게이트를 사용하여 이중 전기 하드리미터를 구현하였다. 서로 다른 파장을 갖는 레이저 다이오드와 FPGA를 이용한 전기 상관기로서 시간과 파장영역의 2차원으로 부호 다중화된 동시 가입자 신호에서 특정 가입자의 신호를 복원하였고, 제한 검출기와 위치 검출기의 이중 전기 하드리미터를 이용하여 MAI로 인한 기존 OCDMA 시스템에서의 식별력 저하와 비트오류 문제를 해결하였다.

• Annual Conference of KIPS
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• 2012.11a
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• pp.652-654
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• 2012

본 논문에서는 다중 심도 카메라 기반의 실시간 피플 카운팅 시스템을 제안 한다. 카메라 영상으로부터 사람을 감지하고 추적하는 시스템 및 그 방법에 관한 것으로, 피플 카운팅 시스템은 쇼핑몰이나 대형건물의 출입구 등과 같은 다양한 환경에 적용될 수 있다. 기존 피플 카운팅 시스템에서의 급격한 조명의 변화나 겹침 현상, 가림 현상에 대한 해결 방법으로, 다중 심도 카메라 환경에서 동일 객체 추적을 위해 RLM(Range Laser Method)를 적용하고, 조명 등 환경 변화에 강인한 배경 제거 및 물체 검출 기법으로 가우시안 혼합 모델(Gaussian Mixture Model)을 적용해 객체인식에 대한 정확도를 높인다. 또한, 객체를 블랍(Blob)으로 지정해 확장 칼만 필터(Extended Kalman Filter, EKF) 방법으로 객체를 추적한다. 본 제안은 피플 카운팅 시스템에의 객체 검출 및 인식에 대한 정확도를 향상시킬 수 있으리라 기대된다.

• Annual Conference of KIPS
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• 2013.05a
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• pp.342-345
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• 2013

본 논문은 모바일 환경에서의 다중생체인식을 통한 개인인증 시스템을 제안한다. 다중생체인식을 위하여 얼굴인식과 화자인식을 선택하였으며, 시스템의 인식 시나리오는 다음을 따른다. 얼굴인식을 위하여 Modified census transform (MCT) 기반의 얼굴검출과 k-means 클러스터 분석 (cluster analysis) 알고리즘 기반의 눈 검출을 통해 얼굴영역 전처리를 수행하고, principal component analysis (PCA) 기반의 얼굴인증 시스템을 구현한다. 화자인식을 위하여 음성의 끝점 추출과 Mel frequency cepstral coefficient(MFCC) 특징을 추출하고, dynamic time warping (DTW) 기반의 화자 인증 시스템을 구현한다. 그리고 각각의 생체인식을 본 논문에서 제안된 방법을 기반으로 융합하여 인식률을 향상시킨다.