• 한국항공우주학회지
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• 제39권9호
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• pp.848-857
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• 2011

영상센서 기반의 충돌회피 시스템을 구성하기 위해서는 수 픽셀 이내의 낮은 신호대잡음비 환경에서 다수의 표적을 탐지할 수 있는 알고리듬이 필요하다. 이처럼 영상 내에서 희미하게 나타나는 잠재적인 표적과 잡음을 구분하기 위한 방법으로서 연속적인 영상 정보를 효율적으로 처리하는 Track-Before-Detect (TBD) 알고리듬이 연구되고 있다. 본 논문에서는 기존의 TBD 알고리듬을 확장하여 다수 표적 탐지 요구조건을 만족시키기 위한 두 가지 방식의 기법을 제시하였다. 첫 번째 방식은 동적 계획법과 K-평균 클러스터링 기법에 기반을 두고 있으며 두 번째 방식은 은닉 마르코프 모델에 Sub-Window 기법을 적용하였다. 제안한 방식의 성능 및 차이점은 수치해석 결과를 통해 분석하였다.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.745-755
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• 2023

The wire rope is an indispensable production machinery in coal mines. It is the main force-bearing equipment of the underground traction system. Accurate detection of wire rope defects and positions exerts an exceedingly crucial role in safe production. The existing defect detection solutions exhibit some deficiencies pertaining to the flexibility, accuracy and real-time performance of wire rope defect detection. To solve the aforementioned problems, this study utilizes the camera to sample the wire rope before the well entry, and proposes an object based on YOLOv5. The surface small-defect detection model realizes the accurate detection of small defects outside the wire rope. The transfer learning method is also introduced to enhance the model accuracy of small sample training. Herein, the enhanced YOLOv5 algorithm effectively enhances the accuracy of target detection and solves the defect detection problem of wire rope utilized in mine, and somewhat avoids accidents occasioned by wire rope damage. After a large number of experiments, it is revealed that in the task of wire rope defect detection, the average correctness rate and the average accuracy rate of the model are significantly enhanced with those before the modification, and that the detection speed can be maintained at a real-time level.

• 한국멀티미디어학회논문지
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• 제15권11호
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• pp.1305-1318
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• 2012

영상분할은 영상 처리 및 패턴 인식에서 매우 어려운 전처리 과정 중 하나이다. 일반적으로는 단순하고 구현이 쉽기 때문에 OTSU의 방법이 많이 사용되고 있지만, 영상의 히스토그램이 단일 분포를 갖거나 단일 분포에 가까울 경우에는 영상 분할이 정확히 되지 못한다. 또한, 만일 표적이 영상에 비해서 소형인 경우 표적의 히스토그램 분포가 작아져서 단일 분포에 가까워진다. 본 논문에서는 소형 표적 검출을 위한 개선된 영상 분할 기법을 제안하였다. 단일 분포 히스토그램의 단점을 극복하기 위하여 배경 히스토그램의 영향을 감소시키는 기법을 적용하였으며, SNR을 높이기 위하여 지역 평균화 기법을 1D OTSU에 적용하였다. 실제 열 영상을 기반으로 실험을 수행한 결과 2D OTSU 방법에 비해서 연산 시간은 크게 줄었으며, 영상 분할 결과는 개선되었음을 확인하였다.

• Journal of Microbiology and Biotechnology
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• 제34권6호
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• pp.1222-1228
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• 2024

Protein-specific antibodies are essential for various aspects of protein research, including detection, purification, and characterization. When specific antibodies are unavailable, protein tagging is a useful alternative. Small epitope tags, typically less than 10 amino acids, are widely used in protein research due to the simple modification through PCR and reduced impact on the target protein's function compared to larger tags. The 2B8 epitope tag (RDPLPFFPP), reported by us in a previous study, has high specificity and sensitivity to the corresponding antibody. However, when attached to the C-terminus of the target protein in immunoprecipitation experiments, we observed a decrease in detection signal with reduced immunity and low protein recovery. This phenomenon was not unique to 2B8 and was also observed with the commercially available Myc tag. Our study revealed that C-terminal tagging of small epitope tags requires the addition of more than one extra amino acid to enhance (restore) antibody immunities. Moreover, among the amino acids we tested, serine was the best for the 2B8 tag. Our findings demonstrated that the interaction between a small epitope and a corresponding paratope of an antibody requires an extra amino acid at the C-terminus of the epitope. This result is important for researchers planning studies on target proteins using small epitope tags.

• Parasites, Hosts and Diseases
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• 제47권3호
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• pp.293-297
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• 2009

Improved methods for detection of Cryptosporidium oocysts in environmental and clinical samples are urgently needed to improve detection of cryptosporidiosis. We compared the sensitivity of 7 PCR primer sets for detection of Cryptosporidium parvum. Each target gene was amplified by PCR or nested PCR with serially diluted DNA extracted from purified C. parvum oocysts. The target genes included Cryptosporidium oocyst wall protein (COWP), small subunit ribosomal RNA (SSU rRNA), and random amplified polymorphic DNA. The detection limit of the PCR method ranged from $10^3$ to $10^4$ oocysts, and the nested PCR method was able to detect $10^0$ to $10^2$ oocysts. A second-round amplification of target genes showed that the nested primer set specific for the COWP gene proved to be the most sensitive one compared to the other primer sets tested in this study and would therefore be useful for the detection of C. parvum.

• 한국군사과학기술학회지
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• 제23권3호
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• pp.204-212
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• 2020

For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

• 전기학회논문지
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• 제68권1호
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• pp.153-158
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• 2019

In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.

• 융합신호처리학회논문지
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• 제14권1호
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• pp.33-38
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• 2013

본 논문은 적외선 연속 영상에서 배경 추정 필터와 칼만 필터, 평균 이동 알고리즘을 사용하여 다중 소형 표적들의 소멸과 생성시에도 표적들의 위치를 추적하는 시스템을 제안한다. 배경 추정 영상파 원 영상과의 차 영상을 사용해서 정지 영상에서의 표적 후 정보를 구하고, 칼만 필터와 후보 표적의 분류를 이용하여 다중 표적을 추적 한다. 마지막으로 평균 이동 알고리즘을 사용하여 표적들의 세부 위치를 조정한다. 실험을 통하여 배경 추정 필터들의 성능을 비교 분석하였고, 제안하는 알고리즘이 기존의 추적 시스템과 비교하여 안정적으로 추적이 됨을 확인하였다.

• 한국전자파학회논문지
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• 제28권8호
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• pp.661-669
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• 2017

본 논문에서는 잠망경을 탐지할 수 있는 항공용 레이다를 이용한 MMTI(Maritime Moving Target Indicator)에 대해 기술한다. 먼저 해상 클러터와 해상 표적의 특성을 알아보고, GMTI(Ground Moving Target Indicator)와 MMTI의 차이를 분석하여, 최적의 MMTI 운용환경 및 운용방법을 제안한다. 그리고 저속의 작은 해상 표적을 탐지하기 위하여 STAP(Space-Time Adaptive Processing)을 활용한 신호처리 알고리즘을 제시한다. 시뮬레이션을 통해 다양한 RCS에 대한 2채널 시스템과 3채널 시스템의 최소탐지속도 탐지확률을 분석하고, 거리 정확도, 속도 정확도, 방위각 정확도와 같은 주요 성능 변수를 분석한다.

• 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.