• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.159-162
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• 2001

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

• Journal of Microbiology and Biotechnology
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• 제33권1호
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• pp.83-95
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• 2023

These days, bacterial detection methods have some limitations in sensitivity, specificity, and multiple detection. To overcome these, novel detection and identification method is necessary to be developed. Recently, NGS panel method has been suggested to screen, detect, and even identify specific foodborne pathogens in one reaction. In this study, new NGS panel primer sets were developed to target 13 specific virulence factor genes from five types of pathogenic Escherichia coli, Listeria monocytogenes, and Salmonella enterica serovar Typhimurium, respectively. Evaluation of the primer sets using singleplex PCR, crosscheck PCR and multiplex PCR revealed high specificity and selectivity without interference of primers or genomic DNAs. Subsequent NGS panel analysis with six artificially contaminated food samples using those primer sets showed that all target genes were multi-detected in one reaction at 10⁸-10⁵ CFU of target strains. However, a few false-positive results were shown at 10⁶-10⁵ CFU. To validate this NGS panel analysis, three sets of qPCR analyses were independently performed with the same contaminated food samples, showing the similar specificity and selectivity for detection and identification. While this NGS panel still has some issues for detection and identification of specific foodborne pathogens, it has much more advantages, especially multiple detection and identification in one reaction, and it could be improved by further optimized NGS panel primer sets and even by application of a new real-time NGS sequencing technology. Therefore, this study suggests the efficiency and usability of NGS panel for rapid determination of origin strain in various foodborne outbreaks in one reaction.

• Journal of electromagnetic engineering and science
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• 제10권4호
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• pp.250-255
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• 2010

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• 반도체디스플레이기술학회지
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• 제17권2호
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• pp.67-70
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• 2018

Object detection and tracking is an exciting and interesting research area in the field of computer vision, and its technologies have been widely used in various application systems such as surveillance, military, and augmented reality. This paper proposes and implements a novel and more robust object recognition and tracking system to localize and track multiple objects from input images, which estimates target state using the likelihoods obtained from multiple CNNs. As the experimental result, the proposed algorithm is effective to handle multi-modal target appearances and other exceptions.

• 한국전자파학회논문지
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• 제27권3호
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• pp.307-316
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• 2016

다층 방어 시스템은 표적의 장거리 조기탐지를 위해 조기 경보 레이다를 활용하고, 정밀 요격 통제를 위해 대공 레이다를 활용하는 방식을 취한다. 그러므로 레이다들 사이에 표적 인계 과정을 필요로 하게 되는데, 추적의 안정화 및 교전 통제를 고려하여 적절한 시점에 표적 인계가 이루어져야 한다. 본 논문에서는 다층 레이다 시스템의 운용 특성을 분석하고, 고속표적에 효과적으로 대응하기 위한 추적 성능 예측 기반의 표적 인계 시점 결정기법을 제안하였다. 또한, 탄도탄 방어 시나리오를 포함하는 통합 시뮬레이터 환경에서 제안 기법을 검증하였다.

• 한국컴퓨터정보학회논문지
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• 제17권10호
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• pp.43-53
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• 2012

본 논문에서는 화면상 약속된 동작을 찾고 추적하는 알고리즘을 이용한 사용자 인터페이스를 제안한다. 현재 frame과 복수의 이전 frame간의 차영상을 이용하여 움직임 영역을 검출하고 약속된 제스처를 취하는 영역을 제어대상으로 인식한다. 이를 통하여 사용자가 장갑을 사용한다던지, 인종, 피부색등에 구애받지 않고 손동작 영역을 검출해 낼 수 있다. 또한 기존 색체 분포 추적 알고리즘을 개량하여 유사한 배경을 가로지르는 경우의 무게중심 위치의 정확성을 높였다. 그 결과 기존 피부색 인식 방법에 비해 약속된 손동작 인식률의 향상이 있었으며 기존 색체 추적 알고리즘에 비교하여 추적 인식률 향상을 확인할 수 있었다.

• 한국통신학회논문지
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• 제22권7호
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• pp.1550-1558
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• 1997

In this paper, we first propose a modified OS CFAR detector called the order statistics cell averaging(OSCA) CFAR detector and anlyze its performance for a Rayleigh target in homogeneous backgrounds, clutter edges, and satistics smallest of(OSSO) CFAR detectors for a Rayleigh target to nonhomogeneous environments. Computer simulation results show that the OSCA CFAR detector has superior performance to OS, OSGO, and OSSO CFAR detectors in homogeneous and multiple target environments. And the proposed detector shows its robustness for fast detection because it requires falf the processing time of the OS CFAR detector.

• ETRI Journal
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• 제43권1호
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• 전자공학회논문지
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• 제51권8호
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• pp.114-125
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• 2014

LFM 신호를 이용하여 속도가 변화하는 표적의 존재 유무를 검출하는 기존의 소나시스템에서는 다수의 LFM 도플러 상관기를 통해 얻은 결과들을 시간상에서 정렬시킨 후 최대값을 테스트 셀로 선택하여 사용한다. 이때 정밀한 표적 검출을 하기 위해서는 많은 수의 LFM 도플러 상관기들이 필요하며, 이로 인해 요구되는 연산량과 메모리도 역시 증가하게 되어 정밀한 LFM 표적 검출기를 실제 구현하는 것을 어렵게 한다. 본 논문에서는 LFM 신호를 사용하는 소나시스템에서 표적 속도 변화에 강인하면서도 고속으로 표적 존재 유무를 검출하기 위한 새로운 기법을 제안하였다. 제안하는 기법에서는 많은 수의 LFM 도플러 상관기들의 정렬된 결과를 합하여 테스트 셀을 만들었으며, 이를 통해 SNR을 향상시킬 뿐만 아니라 표적 속도 변화에 강인한 SNR 값을 제공하여 검출기의 성능을 향상시킨다. 또한 제안하는 기법은 많은 수의 LFM 도플러 상관기들의 정렬된 결과를 합하는 과정을 하나의 합필터로 구현하여 연산량을 획기적으로 줄임으로써 표적을 고속으로 검출할 수 있게 하였다.