• 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.

• 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.

• 한국정보전자통신기술학회논문지
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• 제6권2호
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 한국정보전자통신기술학회논문지
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• 제7권1호
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• pp.61-67
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• 2014

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 공학논문집
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• 제3권1호
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• pp.43-46
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• 1998

지난 30년간 부가 잡음에 의해 열화된 음성신호의 개선에 관해 많은 연구가 진행되어 왔다. 잡음제거를 위한 고전적인 방법인 spectral subtraction, Wiener filter와 최근에 제안된 심리음향모델에 근거한 perceptual filter, EVRC의 잡음제거단을 성능과 구현의 복잡도 측면에서 비교하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.293-294
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• 2007

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 study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Here we select two evaluation methods and make clear the effectiveness of multi-resolutional filter on an energy subtraction image.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.31-38
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• 2009

A process of identifying moving objects from data is typical task in many computer vision applications. In this paper, we propose a motion segmentation method that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modelling. To demonstrate the effectiveness of proposed approach, we tested it gray-scale video data as well as RGB color space.

• 한국안전학회지
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• 제12권3호
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• pp.60-66
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• 1997

In this paper, a moving object surveillance system, which can extract moving object in real-time, using image subtraction method is described. This technique based on the novelty filter having the structure of neural network associative memory. Digital arithmetic and timing control parts were composed of hardwired controller to treat two-dimensional massive image information. SRAMS having 20 ns access time were used for the image buffer that has high speed write/read property. Image extraction algorithm is discussed and supported by simulation and experiments.

• 한국전자통신학회논문지
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• 제8권4호
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• pp.555-560
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• 2013

본 논문에서는 거리측정, 로그전력, 실효치 방법에 의하여 유성음, 무성음, 묵음 구간을 검출하여, 서브밴드 필터에 의한 잡음제거 알고리즘을 제안한다. 제안한 알고리즘은 각 프레임에서 서브밴드 필터를 사용하여 잡음으로 오염된 음성신호로부터 백색잡음 및 도로잡음의 스펙트럼을 차감하는 방법이다. 본 실험에서는 Aurora-2 데이터베이스에 포함된 음성신호와 잡음신호를 사용하여 스펙트럼 차감 알고리즘의 결과를 나타낸다. 잡음에 의하여 오염된 음성신호에 대하여 신호대잡음비를 사용하여 본 알고리즘이 유효하다는 것을 확인한다. 실험으로부터 백색잡음에 대하여 평균 2.1 dB, 도로잡음에 대하여 평균 1.91 dB의 출력 신호대잡음비가 개선된 것을 확인할 수 있었다.

• 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.