• 제목/요약/키워드: Automatic thresholding

검색결과 95건 처리시간 0.021초

INVESTIGATION OF REACTOR CONDITION MONITORING AND SINGULARITY DETECTION VIA WAVELET TRANSFORM AND DE-NOISING

  • Kim, Ok-Joo;Cho, Nan-Zin;Park, Chang-Je;Park, Moon-Ghu
    • Nuclear Engineering and Technology
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    • 제39권3호
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    • pp.221-230
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    • 2007
  • Wavelet theory was applied to detect a singularity in a reactor power signal. Compared to Fourier transform, wavelet transform has localization properties in space and frequency. Therefore, using wavelet transform after de-noising, singular points can easily be found. To test this theory, reactor power signals were generated using the HANARO(a Korean multi-purpose research reactor) dynamics model consisting of 39 nonlinear differential equations contaminated with Gaussian noise. Wavelet transform decomposition and de-noising procedures were applied to these signals. It was possible to detect singular events such as a sudden reactivity change and abrupt intrinsic property changes. Thus, this method could be profitably utilized in a real-time system for automatic event recognition(e.g., reactor condition monitoring).

Image Registration for Cloudy KOMPSAT-2 Imagery Using Disparity Clustering

  • Kim, Tae-Young;Choi, Myung-Jin
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.287-294
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    • 2009
  • KOMPSAT-2 like other high-resolution satellites has the time and angle difference in the acquisition of the panchromatic (PAN) and multispectral (MS) images because the imaging systems have the offset of the charge coupled device combination in the focal plane. Due to the differences, high altitude and moving objects, such as clouds, have a different position between the PAN and MS images. Therefore, a mis-registration between the PAN and MS images occurs when a registration algorithm extracted matching points from these cloud objects. To overcome this problem, we proposed a new registration method. The main idea is to discard the matching points extracted from cloud boundaries by using an automatic thresholding technique and a classification technique on a distance disparity map of the matching points. The experimental result demonstrates the accuracy of the proposed method at ground region around cloud objects is higher than a general method which does not consider cloud objects. To evaluate the proposed method, we use KOMPSAT-2 cloudy images.

기계시각을 이용한 박과채소 종자 정렬파종시스템 개발 (Development of an Automatic Seeding System Using Machine Vision for Seed Line-up of Cucurbitaceous Vegetables)

  • 김동억;조한근;장유섭;김종구;김현환;손재룡
    • Journal of Biosystems Engineering
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    • 제32권3호
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    • pp.179-189
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    • 2007
  • Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

복부 CT 영상에서 신장암의 자동추출 (Automatic Detection of Kidney Tumor from Abdominal CT Scans)

  • 김도연;노승무;조준식;김종철;박종원
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제29권11호
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    • pp.803-808
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    • 2002
  • 본 논문은 복부 컴퓨터단층촬영(CT) 영상에서의 자동화된 신장 및 신장암 추출에 관한 연구를 수행하였다. 필름으로 보관된 복부 CT 영상을 디지털화하여 영상분석을 수행하였으며, 명암값에 의한 임계값(Gray-Level Thresholding) 처리 기법을 사용하여 신장만을 분리하였다. 신장암의 샘플영상에 대한 텍스쳐(Texture)분석 결과를 토대로, 대표적인 통계적 모멘트 값인 평균 및 표준 편차값을 동질성 시험 기준으로 삼아 신장암의 SEED를 선택하였다. 선택된 SEED의 중앙 픽셀을 시작점으로 하여, 명암값을 동질성 시험기준으로 사용한 영역확장(Region Growing) 방법을 적용하여 신장암을 추출하였다. GE사의 Hispeed Advantage CT 스캐너를 사용하여 촬영된 9개의 예, 총 113매 영상을 Lumisys LS-40 필름 디지타이저로 디지털화 하여 적용한 결과, 85%의 신장암 추출 민감도를 가진다.

적외선영상에서 질감 특징과 신경회로망을 이용한 표적탐지 (Target Detection Using Texture Features and Neural Network in Infrared Images)

  • 선선구
    • 전자공학회논문지SC
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    • 제47권5호
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    • pp.62-68
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    • 2010
  • 적외선영상에서 표적을 효율적으로 탐지하는 새로운 자동표적탐지 알고리즘을 제안한다. 이 연구의 목적은 실제 야지환경에서 획득된 적외선영상에서 낮은 오경보 확률로 표적의 위치를 정확히 찾는 것이다. 제안한 방법이 기존의 방법과 다른 점은 초기 탐지단계에서 사용되는 모폴로지 필터링 기법을 밝기정보를 갖고 있는 원래 입력 영상이 아닌 가버(Gabor) 응답 영상에 적용한 것과 표적과 클러터를 구분하기 위해 표적의 정확한 윤곽선 추출을 필요로 하지않는 것이다. 제안한 방법은 크게 3단계로 구성된다. 첫째로, 영상에서 돌출된 영역을 찾기 위해 입력영상으로부터 4 방향의 가버 응답을 구하고 픽셀별로 가버응답 합 영상을 구한다. 이 영상에 모폴로지 기법을 적용하여 돌출된 영역의 위치를 찾는다. 둘째로, 원래의 입력영상의 돌출된 영역에서 지역적인 질감특징 정보들을 찾는다. 마지막 단계로, 찾아진 지역적 특징 정보들이 신경회로망인 다층퍼셉트론 (Multi-Layer Perceptron)으로 입력되어 학습된 훈련 데이터들과의 비교를 통해 실제 표적과 클러터를 구분한다. 실험에서는 제안한 방법을 군사용 적외선 영상장비를 사용하여 실제 야지 환경에 획득된 영상에 적용하여 우수성과 실용가능성을 확인한다.

Automatic Photovoltaic Panel Area Extraction from UAV Thermal Infrared Images

  • Kim, Dusik;Youn, Junhee;Kim, Changyoon
    • 한국측량학회지
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    • 제34권6호
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    • pp.559-568
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    • 2016
  • For the economic management of photovoltaic power plants, it is necessary to regularly monitor the panels within the plants to detect malfunctions. Thermal infrared image cameras are generally used for monitoring, since malfunctioning panels emit higher temperatures compared to those that are functioning. Recently, technologies that observe photovoltaic arrays by mounting thermal infrared cameras on UAVs (Unmanned Aerial Vehicle) are being developed for the efficient monitoring of large-scale photovoltaic power plants. However, the technologies developed until now have had the shortcomings of having to analyze the images manually to detect malfunctioning panels, which is time-consuming. In this paper, we propose an automatic photovoltaic panel area extraction algorithm for thermal infrared images acquired via a UAV. In the thermal infrared images, panel boundaries are presented as obvious linear features, and the panels are regularly arranged. Therefore, we exaggerate the linear features with a vertical and horizontal filtering algorithm, and apply a modified hierarchical histogram clustering method to extract candidates of panel boundaries. Among the candidates, initial panel areas are extracted by exclusion editing with the results of the photovoltaic array area detection. In this step, thresholding and image morphological algorithms are applied. Finally, panel areas are refined with the geometry of the surrounding panels. The accuracy of the results is evaluated quantitatively by manually digitized data, and a mean completeness of 95.0%, a mean correctness of 96.9%, and mean quality of 92.1 percent are obtained with the proposed algorithm.

Directional Particle Filter Using Online Threshold Adaptation for Vehicle Tracking

  • Yildirim, Mustafa Eren;Salman, Yucel Batu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권2호
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    • pp.710-726
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    • 2018
  • This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

온-오프 형태의 DNA 마이크로어레이 영상 분석을 위한 비선형 정합도 (Nonlinear matching measure for the analysis of on-off type microarray image)

  • 류문호;김종대
    • 한국통신학회논문지
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    • 제30권3C호
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    • pp.112-118
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    • 2005
  • 본 논문에서는 교잡반응된 스팟을 템플릿 정합법으로 감지하는 온-오프 형태의 DNA 마이크로어레이 영상의 자동분석을 위한 새로운 비선형 정합도를 제안한다. HPV DNA 칩의 목표 스팟은 인유두종 바이러스(HPV)의 종을 알아내기 위해서 설계된다. 제안하는 척도는 전체 템플릿 영역을 이진 문턱값으로 양극화하여 스팟 영역 내의 밝은 화소의 개수를 취해서 얻는다. 이 척도를 추정된 마커 위치의 정확도 관점에서 평가하여 정규화된 상관도보다 우수함을 보인다.

Urban Road Extraction from Aerial Photo by Linking Method

  • Yang, Sung-Chul;Han, Dong-Yeo;Kim, Min-Suk;Kim, Yong-Il
    • Korean Journal of Geomatics
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    • 제3권1호
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    • pp.67-72
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    • 2003
  • We have seen rapid changes in road systems and networks in urban areas due to fast urbanization and increased traffic demands. As a result, many researchers have put greater importance on extraction, correction and updating of information about road systems. Also, by using the various data on road systems and its condition, we can manage our road more efficiently and economically. Furthermore, such information can be used as input for digital map and GIS analysis. In this research, we used a high resolution aerial photo of the roads in Seongnam area. First, we applied the top-hat filter to the area of interest so that the road markings could be extracted in an efficient manner. The lane separation lines were selected, considering the shape similarity between the selected lane separation line and reference data. Next, we extracted the roads in the urban area using the aforementioned road marking. Using this technique, we could easily extract roads in urban area in semi-automatic way.

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레이저 파면 획득용 Lenslet Array 점 패턴 검출 알고리즘 (Detection Algorithm of Lenslet Array Spot Pattern for Acquisition of Laser Wavefront)

  • 이재일;이영철;허준
    • 한국군사과학기술학회지
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    • 제8권4호
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    • pp.110-119
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    • 2005
  • In this paper, a new detection algorithm was proposed for finding the position of lenslet array spot pattern used to acquire laser wavefront. Based on the analysis of the required signal processing characteristics, we categorized into and designed four main signal processing functions. The proposed was designed in order to have robust feature against a variation of geometrical form of the spot and also implemented to have semi-automatic thresholding capability based on CCD noise analysis. For performance evaluation, we made qualitative and quantitative comparisons with Carvalho's algorithm which has been published in recent. In the given experimental spot images, the proposed could detect the spots which has 1/3 times lower than the least S/N of which Carvalho's can detect and could reach to a detection precision of 0.1 pixel at the S/N. In functional aspect, the proposed could separate all valid spots locally. From these results, the proposed could have a superior precision of location detection of spot pattern in wider S/N range.