• Title/Summary/Keyword: 임계 값

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A Scene Change Detection Technique using the Weighted $\chi^2$-test and the Automated Threshold-Decision Algorithm (변형된 $\chi^2$- 테스트와 자동 임계치-결정 알고리즘을 이용한 장면전환 검출 기법)

  • Ko, Kyong-Cheol;Rhee, Yang-Won
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.42 no.4 s.304
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    • pp.51-58
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    • 2005
  • This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision at algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.

Gradual Scene Transition Detection using Summation of Feature Difference Area (특징값 비유사도 영역의 누적 분포를 이용한 점진적 장면전환 검출)

  • Lee Jong-Myoung;Kim Myoung-Joon;Seo Byeong-Rak;Kim Whoi-Yul
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.877-879
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    • 2005
  • 장면전환의 검출은 비디오 브라우징, 검색, 요약 등에 관한 많은 응용에 유용하다. 본 논문에서는 점진적 장면전환 검출을 위해 정의된 N-길이 로컬 윈도우 내에서 비유사도 분포가 갖는 최소값만큼 상승하여 형성되는 분포를 구하고, 분포의 상단이 이루는 비유사도 값을 누적하여 설정된 임계값보다 클 경우 점진적 장면전환으로 판단하는 방법을 제안한다. 장면전환 구간에서 이루는 영역의 누적값은 최소-최대 분포를 이용하여 구할 수 있다. 실험에서 기존의 제안된 방법과 비교를 하였고 그 결과 제안된 방법에서 올바른 장면전환 검출 성능은 낮았으나 잘못 검출되는 장면전환 수는 적은 결과를 보였다. 제안된 방법은 점진적 장면전환 검출을 위한 임계값의 선택이 쉬우며, 장면전환 길이에 크게 의존하지 않는 장점이 있고 수행속도가 높아 실시간으로 처리하는데 적합하다.

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Sentinel-1 SAR image-based waterbody detection technique for estimating the water storage in agricultural reservoirs (농업저수지의 저수량 추정을 위한 Sentinel-1 SAR 영상 기반 수체탐지 기법)

  • Jeong, Jaehwan;Oh, Seungcheol;Lee, Seulchan;Kim, Jinyoung;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.54 no.7
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    • pp.535-544
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    • 2021
  • Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

Detecting Space-Time Clusters in Linear Point Data (선형 점자료에 있어서의 시.공 복합 군집의 탐색)

  • 홍상기
    • Journal of the Korean Geographical Society
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    • v.33 no.2
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    • pp.325-338
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    • 1998
  • 본 연구에서는 시.공 복합적인 선형 점 자료를 대상으로 시간과 공간을 함께 고려했을 때 자료 내에 군집(cluster)-시.공 복합 군집(space-time cluster)-이 존재하는 가를 검증하는 방법에 대해 논의하고, 실제 교통사고지점의 분포자료를 분석하여 군집의 유무를 통계적으로 검증하였다. 통계 분석의 결과 다음과 같은 사실이 확인되었다. 첫째, Knox의 분할표 방법과 Mantel의 역수 변환을 이용한 일반화된 회귀분석방법 모두 임계 거리 및 임계 시간 간격의 선택이 분석결과에 영향을 미친다. 둘째, 이러한 임의성을 극복하기 위해 다양한 임계 거리 및 임계 시간 간격(혹은 부가 상수)에 대해 반복 실험한 결과, 일부 임계값의 조합에서 시간과 공간이 서로 독립적이라는 귀무가설을 기각할 수 있는 증거가 발견되었다. 셋째, 시.공 복합 군집의 파악에 가장 적합한 임계 거리와 임계 시간 간격은 공간적으로는 7000m, 시간적으로는 14일 혹은 21일이다. 마지막으로, 통계 분석과정에서 자료에 존재하는 중복 기록 사고들의 존재가 밝혀짐으로써 시.공 복합군집 검증이 탐험적 자료 분석(exploratory data analysis)의 도구로서 가지는 가치를 확인할 수 있었다.

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Enhanced Fuzzy Binary Method using FCM Algorithm (FCM 알고리즘을 이용한 개선된 퍼지 이진화 방법)

  • Park, Ha-Sil;Song, Doo Heon;Kim, Kwang-Beak
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.145-147
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    • 2014
  • 대부분 이진화 알고리즘은 임계치를 결정하기 위해 히스토그램을 사용하여 밝기 분포를 분석한다. 배경과 물체의 명암 차이가 큰 경우는 분할을 위해 양봉 히스토그램으로 표현하여 최적의 임계치를 찾기 위해 히스토그램 골짜기를 선택하는 것으로도 양호한 임계치를 찾을 수 있지만 배경과 물체의 밝기 차이가 크지 않거나 밝기 분포가 양봉 특성을 보이지 않을 때는 히스토그램 분석만으로 적절한 임계치를 얻기 어렵다. 이 문제점을 개선하기 위해 삼각형 타입의 소속 함수를 적용하여 임계치를 동적으로 설정하고 영상을 이진화 하는 퍼지 이진화 방법이 제안되었다. 퍼지 이진화 방법은 소속 함수에 적용된 소속도를 a-cut에 적용하여 영상을 이진화 한다. 그러나 기존의 퍼지 이진화 방법은 a-cut값을 경험적으로 설정하기 때문에 다양한 영상을 이진화하는 과정에서 정보 손실이 많이 발생하는 문제점이 있다. 따라서 본 논문에서는 FCM 클러스터링 알고리즘을 이용하여 퍼지 이진화 방법의 a-cut값을 동적으로 설정하여 이진화하는 방법을 제안한다. 제안된 방법을 다양한 영상에 적용한 결과, 배경과 물체의 명암도 차이가 크게 나지 않는 영상의 경우에는 기존의 퍼지 이진화 방법보다 정보 손실이 적은 상태로 이진화되는 것을 확인하였다.

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Unsupervised Change Detection of Hyperspectral images Using Range Average and Maximum Distance Methods (구간평균 기법과 직선으로부터의 최대거리를 이용한 초분광영상의 무감독변화탐지)

  • Kim, Dae-Sung;Kim, Yong-Il;Pyeon, Mu-Wook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.1
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    • pp.71-80
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    • 2011
  • Thresholding is important step for detecting binary change/non-change information in the unsupervised change detection. This study proposes new unsupervised change detection method using Hyperion hyperspectral images, which are expected with data increased demand. A graph is drawn with applying the range average method for the result value through pixel-based similarity measurement, and thresholding value is decided at the maximum distance point from a straight line. The proposed method is assessed in comparison with expectation-maximization algorithm, coner method, Otsu's method using synthetic images and Hyperion hyperspectral images. Throughout the results, we validated that the proposed method can be applied simply and had similar or better performance than the other methods.

Robust Threshold Determination on Various Lighting for Marker-based Indoor Navigation (마커 방식 실내 내비게이션을 위한 조명 변화에 강한 임계값 결정 방법)

  • Choi, Tae-Woong;Lee, Hyun-Cheol;Hur, Gi-Taek;Kim, Eun-Seok
    • The Journal of the Korea Contents Association
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    • v.12 no.1
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    • pp.1-8
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    • 2012
  • In this paper, a method of determining the optimal threshold in image binarization for the marker recognition is suggested to resolve the problem that the performances of marker recognition are quite different according to the changes of indoor lighting. The suggested method determines the optimal threshold by considering the average brightness, the standard deviation and the maximum deviation of video image under the various indoor lighting circumstances, such as bright light, dim light, and shadow by unspecified obstacles. In particular, the recognition under the gradation lighting by shadow is improved by applying the weighted value that depends on the brightness of image. The suggested method is experimented to process $720{\times}480$ resolution video images under the various lighting environments, and it shows the fast and high performance, which is suitable for mobile indoor navigation.

Threshold based User-centric Clustering for Cell-free MIMO Network (셀프리 다중안테나 네트워크를 위한 임계값 기반 사용자 중심 클러스터링)

  • Ryu, Jong Yeol;Lee, Woongsup;Ban, Tae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.114-121
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    • 2022
  • In this paper, we consider a user centric clustering in order to guarantee the performance of the users in cell free multiple-input multiple-output (MIMO) network. In the user centric clustering scheme, by using large scale fading coefficients of the connected access points (APs), each user decides own cluster with the APs having the higher the large scale fading coefficients than threshold value compared to the highest large scale fading coefficient. In the determined user centric clusters, the APs design the beamformers and power allocations in the distributed manner and the APs cooperatively transmit data to users by using beamformers and power allocations. In the simulation results, we verify the performance of user centric clustering in terms of the spectral efficiency and we also find the optimal threshold value in the given configuration.

Video Segmentation Method using Improved Adaptive Threshold Algorithm and Post-processing (개선된 적응적 임계값 결정 알고리즘과 후처리 기법을 적용한 동영상 분할 방법)

  • Won, In-Su;Lee, Jun-Woo;Lim, Dae-Kyu;Jeong, Dong-Seok
    • Journal of Korea Multimedia Society
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    • v.13 no.5
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    • pp.663-673
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    • 2010
  • As a tool used for video maintenance, Video segmentation divides videos in hierarchical and structural manner. This technique can be considered as a core technique that can be applied commonly for various applications such as indexing, abstraction or retrieval. Conventional video segmentation used adaptive threshold to split video by calculating difference between consecutive frames and threshold value in window with fixed size. In this case, if the time difference between occurrences of cuts is less than the size of a window or there is much difference in neighbor feature, accurate detection is impossible. In this paper, Improved Adaptive threshold algorithm which enables determination of window size according to video format and reacts sensitively on change in neighbor feature is proposed to solve the problems above. Post-Processing method for decrement in error caused by camera flash and fast movement of large objects is applied. Evaluation result showed that there is 3.7% improvement in performance of detection compared to conventional method. In case of application of this method on modified video, the result showed 95.5% of reproducibility. Therefore, the proposed method is more accurated compared to conventional method and having reproducibility even in case of various modification of videos, it is applicable in various area as a video maintenance tool.

The Threshold Based Cluster Head Replacement Strategy in Sensor Network Environment (센서 네트워크 환경의 임계값 기반 클러스터 헤드 지연 교체 전략)

  • Kook, Joong-Jin;Ahn, Jae-Hoon;Hong, Ji-Man
    • Journal of Internet Computing and Services
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    • v.10 no.3
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    • pp.61-69
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    • 2009
  • Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing life-time of wireless sensor networks. In this paper, we present the threshold based cluster head replacement strategy for clustering protocols in wireless sensor networks. This protocol minimizes the number of cluster head selection by preventing the cluster head replacement up to the threshold of residual energy. Reducing the amount of head selection and replacement cost, the life-time of the entire networks can be extended compared with the existing clustering protocols. Our simulation results show that our protocol outperformed than LEACH in terms of balancing energy consumption and network life-time.

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