• 제목/요약/키워드: Subtraction

검색결과 1,038건 처리시간 0.034초

에너지 차분 흉부 X선 화상으로부터 폐종류 음영 검출 필터의 평가 (Evaluation of Pulmonary Nodules Finer on Energy Subtraction X-ray Images)

  • 김응규;이충호;권영도
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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    • pp.61-64
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    • 2000
  • The purpose of this study is prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we examine influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images and evaluation methods. As one type of images, we select energy subtraction X-ray images, at the same time is done ▽$^2$G filter and multi-resolutional filter. Here select two evaluation methods and make clear the effectiveness of multi-resolutional filter on an energy subtraction image.

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Probabilistic Background Subtraction in a Video-based Recognition System

  • Lee, Hee-Sung;Hong, Sung-Jun;Kim, Eun-Tai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권4호
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    • pp.782-804
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    • 2011
  • In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

A study on the column subtraction method applied to ship scheduling problem

  • Hwang, Hee-Su;Lee, Hee-Yong;Kim, Si-Hwa
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2004년도 춘계학술대회 논문집
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    • pp.401-405
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    • 2004
  • Column subtraction, originally proposed by Harche and Thompson(]994), is an exact method for solving large set covering, packing and partitioning problems. Since the constraint set of ship scheduling problem(SSP) have a special structure, most instances of SSP can be solved by LP relaxation. This paper aims at applying the column subtraction method to solve SSP which can not be solved by LP relaxation. For remained instances of unsolvable ones, we subtract columns from the finale simplex table to get another integer solution in an iterative manner. Computational results having up to 10,000 0-1 variables show better performance of the column subtraction method solving the remained instances of SSP than complex branch-and-bound algorithm by LINDO.

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두부방사선 계측과 Photographic subtraction을 이용한 측모 두부방사선 규격사진의 재현성에 관한 연구 (EVALUATION OF THE REPRODUCIBILITY IN CEPHALOGRAPHY USING ROENTGENOCEPHALOMETRICS AND PHOTOGRAPHIC SUBTRACTION)

  • 전선두;나경수
    • 치과방사선
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    • 제24권2호
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    • pp.347-359
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    • 1994
  • The reproducibility of cephalography in repeated exposures were studied by tracing and photographic subtraction. The materials consisted of 50 pairs of 'same day' radiograph taken under identical conditions. The evaluation included skull, cervical column, hyoid bone, pharynx, tongue, soft tissue profile resulting 43 items in tracing, and 19 items in photographic subtraction. The results obtained from the differences between each pair were as follows: 1. The means and standard deviations by tracing of skull, cervical column, hyoid bone, pharynx, tongue, soft tissue profile were 0.34±0.62㎜, 1.02±1.59㎜, 1.37±1.78㎜, 0.55±1.16㎜, 0.51±1.51㎜, 0.15±0.3㎜ each. 2. The means and standard deviations by photographic subtraction of skull, cervical column, hyoid bone, pharynx, tongue were 0.09±0.35㎜, 0.70±0.95㎜, 1.22±1.33㎜, 0.53±0.86㎜, 0.27±0.41㎜ each.

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적응 필터를 이용한 청각 자극에 의한 뇌자도 신호에서 노이즈 제거 (Adaptive Noise Subtraction in Auditory Evoked Field)

  • 이동훈;안창범
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권10호
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    • pp.606-610
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    • 2003
  • Noise subtraction using reference channel data has been used to improve signal-to-noise ratio in magnetoencephalography. In this paper, an adaptive noise subtraction model is proposed and parameters for the model are optimized. A criterion to determine an optimal update period for the filter coefficients is proposed based on the ratio of peak amplitude of evoked field (N100m) divided by the output standard deviation. Experiments are carried out using a 40 channel MEG system. From the experiments, the proposed noise subtraction method shows superior performances over existing non-adaptive methods. Two-dimensional topographic map is shown for a diagnosis with a cubic spline interpolation.

축구 동영상 분석을 위한 배경 분리 알고리즘들의 정량적 비교 평가에 관한 연구 (Objective Evaluation of Background Subtraction Algorithms for Soccer Video Analysis: An Experimental Comparative Study)

  • 정찬호
    • 한국통신학회논문지
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    • 제42권1호
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    • pp.42-45
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    • 2017
  • 본 논문에서는 "축구 동영상" 분석을 위한 "최적의" 배경 분리 알고리즘을 결정하기 위하여 정량적인 비교 평가 연구를 수행하였다. 이를 위해 본 논문에서는 다섯 가지 서로 다른 배경 분리 알고리즘을 동일한 실험 환경에서 비교 평가하였다. 정량적인 비교 평가를 위해 Precision, Recall 및 F-measure를 이용하였다. 본 논문에서 제시된 정량적 비교 평가 결과는 지능형 축구 동영상 분석 시스템 개발을 위해 배경 분리 기술을 이용하거나 축구 동영상에 특화된 배경 분리 기술을 연구하고자 하는 연구자 및 개발자들에게 실질적인 도움이 될 것으로 예상된다.

A study on the column subtraction method applied to ship scheduling problem

  • Hwang, Hee-Su;Lee, Hee-Yong;Kim, Si-Hwa
    • 한국항해항만학회지
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    • 제28권2호
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    • pp.129-133
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    • 2004
  • Column subtraction, originally proposed by Harche and Thompson(1994), is an exact method for solving large set covering, packing and partitioning problems. Since the constraint set of ship scheduling problem(SSP) have a special structure, most instances of SSP can be solved by LP relaxation This paper aim, at applying the column subtraction method to solve SSP which am not be solved by LP relaxation For remained instances of unsolvable ones, we subtract columns from the finale simplex table to get another integer solution in an iterative manner. Computational results having up to 10,000 0-1 variables show better performance of the column subtraction method solving the remained instances of SSP than complex branch and-bound algorithm by LINDO.

Multi-Person Tracking Using SURF and Background Subtraction for Surveillance

  • Yu, Juhee;Lee, Kyoung-Mi
    • Journal of Information Processing Systems
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    • 제15권2호
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    • pp.344-358
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    • 2019
  • Surveillance cameras have installed in many places because security and safety is becoming important in modern society. Through surveillance cameras installed, we can deal with troubles and prevent accidents. However, watching surveillance videos and judging the accidental situations is very labor-intensive. So now, the need for research to analyze surveillance videos is growing. This study proposes an algorithm to track multiple persons using SURF and background subtraction. While the SURF algorithm, as a person-tracking algorithm, is robust to scaling, rotating and different viewpoints, SURF makes tracking errors with sudden changes in videos. To resolve such tracking errors, we combined SURF with a background subtraction algorithm and showed that the proposed approach increased the tracking accuracy. In addition, the background subtraction algorithm can detect persons in videos, and SURF can initialize tracking targets with these detected persons, and thus the proposed algorithm can automatically detect the enter/exit of persons.

Research on Noise Reduction Algorithm Based on Combination of LMS Filter and Spectral Subtraction

  • Cao, Danyang;Chen, Zhixin;Gao, Xue
    • Journal of Information Processing Systems
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    • 제15권4호
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    • pp.748-764
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    • 2019
  • In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.