• 한국군사과학기술학회지
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• 제5권3호
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• pp.113-119
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• 2002

A target adaptive guidance(TAG) algorithm is proposed employing the near-zone signal that can be measured from an infrared seeker. The guidance order is composed of a conventional PNG command and an additional command to be calculable from an additional LOS rate between a hot point of target and a required intercept point. The characteristic of the near-zone signal is similar to that of LOS rate that is inversely proportional to the square of time-to-go. Hence the proposed scheme can be applied to real systems with no estimator for time-to-go. From analysis results on the miss distance with perfect missile and perfect seeker, it follows that the proposed TAG algorithm guarantees missile to be ideally guided to the required intercept point. And it is less affected by the TAG start time and a proportional navigation ratio than other TAG schemes using a LOS rate such as a step bias or a ramp bias.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1059-1062
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• 2000

Infrared (IR) seeker identifies the location of a target by detecting the infrared energy radiated from the target, and enables the missile to track the target. To improve the tracking performance, a counter- countermeasure (CCM) is essential to minimize the effect of the countermeasure (CM), which is operated by a target to protect itself. In this paper, we propose a crossed array tracker (CAT) using two-color CCM algorithm. The CAT using the proposed algorithm shows better tracking performance by minimizing the effect of CM.

• 한국컴퓨터정보학회논문지
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• 제21권12호
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• pp.35-41
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• 2016

In this paper, we propose a new real-time dead pixel detection method based on spatial compare filtering, which are usually used in the small target detection. Actually, the soft dead and the small target are cast in the same mold. Our proposed method detect and remove the dead pixels as applying the spatial compare filtering, into the pixel outputs of a detector after the non-uniformity correction. Therefore, we proposed method can effectively detect and replace the dead pixels regardless of the non-uniformity correction performance. In infrared camera, there are usually many dead detector pixels which produce abnormal output caused by manufactural process or operational environment. There are two kind of dead pixel. one is hard dead pixel which electronically generate abnormal outputs and other is soft dead pixel which changed and generated abnormal outputs by the planning process. Infrared camera have to perform non-uniformity correction because of structural and material properties of infrared detector. The hard dead pixels whose offset values obtained by non-uniformity correction are much larger or smaller than the average can be detected easily as dead pixels. However, some dead pixels(soft dead pixel) can remain, because of the difficulty of uncleared decision whether normal pixel or abnormal pixel.

• The Korean Journal of Legal Medicine
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• 제42권4호
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• pp.146-152
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• 2018

We investigated the neural correlates of accurate eyewitness memory retrieval using functional near-infrared spectroscopy. We analyzed oxygenated hemoglobin ($HbO_2$) concentration in the prefrontal cortex during eyewitness memory retrieval task and examined regional $HbO_2$ differences between observed objects (target) and unobserved objects (lure). We found that target objects elicited increased activation in the bilateral ventrolateral prefrontal cortex, which is known for monitoring retrieval processing via bottom-up attentional processing. Our results suggest bottom-up attentional mechanisms could be different during accurate eyewitness memory retrieval. These findings indicate that investigating retrieval mechanisms using functional near-infrared spectroscopy might be useful for establishing an accurate eyewitness recognition model.

• 제어로봇시스템학회논문지
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• 제17권6호
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• pp.579-586
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• 2011

It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.

• 산업기술연구
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• 제34권
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• pp.27-32
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• 2014

Infrared remote controllers are widely used in controlling electronic devices due to its simplicity and convenience. This paper presents a smart phone application unifying any infrared remote controllers. We can select a device from device list menu of the application. Any new device can be added easily by downloading the protocol file of the device from protocol file server. Remote controller protocol files are stored in audio file format, and the file related to a specific menu button is transmitted through the audio jack of smart phones. The protocol file server is a standard file server, and protocol files for various devices are collected by infrared receiver module. For smart phones without infrared facility, a small infrared module translating audio signal to infrared signal is applied.

• 한국통신학회논문지
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• 제35권1C호
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• pp.8-16
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• 2010

본 논문은 적외선 영상 시퀀스 (infrared image sequences)에서 시간적 프로파일 (temporal profile)을 기반으로 한 시간적 화소 (temporal pixel)들의 외적 (cross product)을 사용한 새로운 소형 표적 검출 방법을 제안한다. 소형 표적 및 그 주변배경은 시간적 특성이 서로 다르므로, 시간적 프로파일에서 화소들의 외적을 사용한 가설검증을 통하여 표적 화소 및 배경화소를 구분하고, 그 결과를 기반으로 시간적 배경 (temporal background)을 예측한다. 소형 표적은 원 시간적 프로파일과 예측된 시간적 배경 프로파일의 차에 의해 검출한다. 기존 방법과 제안한 방법의 성능 비교를 위하여, ROC (receiver operating characteristics) 곡선을 실험에서 사용하였다. 실험결과에서 제안된 방법이 기존방법들보다 오경보율 (false alarm rate)이 낮고, 표적 및 배경에 대한 향상된 식별력을 가짐을 확인하였다.

• Journal of the Korean Wood Science and Technology
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• 제42권3호
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• pp.223-230
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• 2014

본 연구는 한지 제조과정에서 특별한 용도가 없어서 버려지는 닥나무 목질부로 밀도 및 수지첨가량별로 파티클보드를 제조하고, 이를 건축마감재로 활용 가능성을 알아보고자 탈취효과, 원적외선 방사 및 실내 공기오염물질 방사특성에 대하여 검토하였다. 측정 결과 보드의 밀도 및 수지첨가량이 증가할수록 탈취율은 증가하였다. 탈취율은 80~90%, 원적외선 방사율은 0.892~0.899로 비교적 높았다. 총휘발성유기화합물은 수지첨가율 13%, 밀도 $0.6g/cm^3$인 보드가 $0.074mg/m^2{\cdot}h$로 가장 적게 방출되었고, 폼알데하이드는 보드 제조 조건별로 $0.004{\sim}0.006mg/m^2{\cdot}h$로 미세한 방출 특성을 보였다. 이와 같이 보드 제조 조건을 다양하게 하여 용도에 맞는 보드제조가 가능하다면, 닥나무 목질부로 제조된 보드는 건축마감재 이용가능성이 있을 것으로 생각된다.

• 한국컴퓨터정보학회논문지
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• 제29권7호
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• pp.41-51
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• 2024

본 논문에서는 적외선 이미지에서 딥러닝 물체 탐지를 사용하여 유도무기의 표적 탐지 정확도 향상 방법을 연구한다. 적외선 이미지의 특성은 시간, 온도 등의 요인에 의해 영향을 받기 때문에 모델을 학습할 때 다양한 환경에서 표적 객체의 특징을 일관되게 표현하는 것이 중요하다. 이러한 문제를 해결하는 간단한 방법은 적절한 전처리 기술을 통해 적외선 이미지 내 표적 객체의 특징을 강조하고 노이즈를 줄이는 것이다. 그러나, 기존 연구에서는 적외선 영상 기반 딥러닝 모델 학습에서 전처리기법에 관한 충분한 논의가 이루어지지 못했다. 이에, 본 논문에서는 표적 객체 검출을 위한 적외선 이미지 기반 훈련에 대한 이미지 전처리 기술의 영향을 조사하는 것을 목표로 한다. 이를 위해 영상과 이미지의 전역(global) 또는 지역(local) 정보를 활용한 적외선 영상에 대한 전처리인 Min-max normalization, Z-score normalization, Histogram equalization, CLAHE (Contrast Limited Adaptive Histogram Equalization)에 대한 결과를 분석한다. 또한, 각 전처리 기법으로 변환된 이미지들이 객체 검출기 훈련에 미치는 영향을 확인하기 위해 다양한 전처리 방법으로 처리된 이미지에 대해 YOLOX 표적 검출기를 학습하고, 이에 대한 분석을 진행한다. 실험과 분석을 통해 전처리 기법들이 객체 검출기 정확도에 영향을 미친다는 사실을 알게 되었다. 특히, 전처리 기법 중에서도 CLAHE 기법을 사용해 실험을 진행한 결과가 81.9%의 mAP (mean average precision)을 기록하며 가장 높은 검출 정확도를 보임을 확인하였다.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1044-1052
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• 2010

In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.