• 한국정보통신학회논문지
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• 제20권9호
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• pp.1673-1678
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• 2016

음성인식처리 분야에서 배경잡음으로 인하여 음성입력이 배경잡음으로 잘못 판단되는 원인이 되어 음성인식율의 저하를 초래한다. 이러한 종류의 잡음대책은 단순하지 않으므로 보다 고도한 잡음처리기술이 필요하게 된다. 따라서 본 논문에서는 잡음환경 중에서 정상적인 배경잡음 혹은 비정상적인 배경잡음과 지속 시간이 짧은 음성을 구별하는 알고리즘에 대하여 기술한다. 본 알고리즘은 다른 종류의 잡음과 음성을 구별하는 중요한 수단으로서 개량된 음성의 특징파리미터를 사용한다. 다음으로 다층퍼셉트론 네트워크에 의하여 잡음의 종류를 추정하는 알고리즘에 대해서 기술한다. 본 실험에서는 잡음과 음성이 구별이 가능하도록 실험적으로 확인하였다.

• 융합신호처리학회논문지
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• 제5권2호
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• pp.106-110
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• 2004

기동하는 잠수함이나 함정 등의 방사 소음 특성은 토날 신호와 광대역 배경잡음으로 구분된다. 토날 신호는 함정의 모터나 엔진의 회전등으로 인한 것이고, 배경잡음은 기동 시 일어나는 함정 주변의 기포들의 발생과 소멸로 인한 것이다. 본 연구에서는 ATW 알고리즘을 이용하여 수중 기동함정의 방사소음을 분석한다. 또한 분석한 소음을 바탕으로 힐버트 변환을 이용하여 광대역 유사 잡음을 발생시킬 수 있는 시스템을 설계하고 분석한 토날 신호를 합성함으로써 유사 방사 잡음 발생 시스템을 설계한다. 이 시스템은 현장 기동함정과 유사한 소음을 발생시키게 함으로써 적으로부터 아군의 함정이 노출되었을 때 기만기로 사용함으로써 적의 어뢰 등의 공격을 피할 수 있는 시스템으로 활용할 수 있을 것이다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.363-366
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• 2005

Social survey and auditory experiment on residential noises such as floor impact, air-bome, bathroom, drainage and traffic noises were conducted to investigate the effects of sensitivity and background noise levels on subjective response to residential noises. Results of survey showed that multiple questions for sensitivity to noise have a more power for discrimination against subjective response to noise than single question. It was also found that the correlation between sensitivity and annoyance was relatively low, but the differences in annoyance between sensitivity groups were significant. Result of auditory experiment showed that effects of sensitivity on annoyance were different according to noise type and noise level. It was also shown that the difference in annoyance between the lowest sensitive stoup and the highest sensitive group was significant in low noise level. The effects of background noise on subjective responses to noise was also different according to noise source and noise level, and were significant in low noise level of airborne and drainage noise.

• Journal of Information Display
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• 제3권2호
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• 말소리와 음성과학
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• 제7권1호
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• pp.27-37
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• 2015

This study was mainly aimed at investigating on the effects of background noises (i.e., white noise, multi-speaker conversational babble) on stuttering rate and other speech-related measures (i.e., articulation rate, speech effort). Nine Korean-speaking adults who stutter participated in the study. Each of the participants was asked to read a series of passages under each of four experimental conditions (i.e., typical solo reading (TR), choral reading (CR), reading under white noise presented (WR), reading with multi-speaker conversational babble presented (BR). Stuttering rate was computed based on a percentage of syllables stuttered (%SS) and articulation rate was also assessed as another speech-related measure under each of the experimental conditions. To examine the amount of physical effort needed to read, the speech effort was measured by using the 9-point Speech Effort Self Rating Scale originally employed by Ingham et al. (2006). Study results showed that there were no significant differences among each of the passage reading conditions in terms of stuttering rate, articulation rate, and speech effort. In conclusion, it can be argued that the two different types of background noises (i.e., white noise and multi-speaker conversational babble) are not different in the extent to which each of them enhances fluency of adults who stutter. Self ratings of speech effort may be also useful in measuring speech-related variables associated with vocal changes induced under each of the fluency enhancing conditions.

• 정보기술응용연구
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• 제3권2호
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• pp.133-147
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• 2001

본 논문에서는, 문자와 그림을 포함한 컬러 영상에서 낮은 명도의 색상으로 인쇄된 문자를 효율적으로 추출하기 위하여, 컬러 영상에 대한 2치화와 잡음을 제거하는 새로운 방법을 제안하였다. 컬러 영상에 포함된 문자를 추출하기 위한 컬러 영상의 2치화는, 입력영상의 배경후보영역과 문자후보영역의 화소수 비에 따라 이 두 영역간의 컬러 관계성을 구하고, 이 관계성과 예비임계값에 의해 계산된 임계값에 의하여 이루어진다. 예비임계값은 입력 영상에 대한 RGB 히스토그램의 분석에 의하여 구하며, 입력영상의 배경후보영역과 문자후보영역의 기준이 된다. 제안한 임계값은 잡음의 양에 따라 동적으로 계산되므로, 문자정보는 최대한 유지하고, 잡음은 효과적으로 제거할 수 있다. 또, 본 연구에서는 2치화 영상에 포함된 잡음의 효과적 제거를 위하여, 다양한 컬러 영상의 2치화 영상에 포함된 잡음패턴을 분석하여 잡음패턴 테이블을 만들었다. 2치화 영상에 포함된 잡음은 잡음패턴 테이블과 템플릿 매칭을 하여 잡음의 분포도가 계산되고, 이 분포도에 의하여 잡음의 난이도를 3단계로 분류하였다. 잡음의 제거는 분류된 난이도에 따라 별개의 처리 과정을 두어 수행하므로, 잡음제거의 효율을 높였고, 처리시간을 줄였다.

• 한국통신학회논문지
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• 제25권1B호
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• pp.112-119
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• 2000

Two-color 적외선 탐색기는 표적의 대응 능력과 배경 잡음이 존재하는 상황에서 효율적인 표적 추적을 위해 두 개의 검출 대역을 사용한다. 본 논문은 Two-color 탐색기의 검출 대역 선정에 관한 연구이다. 검출 대역을 선정하기 위해, 표적, 섬광탄, 및 배경 잡음의 적외선 방사 특성을 분석하고, 수신 전력과 깊이 관련된 대기 투가 특성, 검출 가능 거리, 배경 잡음의 영향, 신호 대 잡음비 등의 특성을 분석한다. 분석 결과, two-color 적외선 탐색기의 적절한 대역은 표적 검출을 위한 3$\mu\textrm{m}$~5$\mu\textrm{m}$ 대역과 반대응 능력을 위한 $1.5\mu\textrm{m}$~1.7$\mu\textrm{m}$ 대역으로 나타났다. 본 논문의 연구 결과는 two-color 탐색기의 추후 연구에 중요한 역할을 할 것이다.

• 스마트미디어저널
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• 제5권1호
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• pp.78-87
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• 2016

The major problems of recent object tracking methods are related to the inefficient detection of moving objects due to occlusions, noisy background and inconsistent body motion. This paper presents a robust method for the detection and tracking of a moving in infrared animal videos. The tracking system is based on adaptive optical flow generation, Gaussian mixture and Kalman filtering. The adaptive Gaussian model of optical flow (GMOF) is used to extract foreground and noises are removed based on the object motion. Kalman filter enables the prediction of the object position in the presence of partial occlusions, and changes the size of the animal detected automatically along the image sequence. The presented method is evaluated in various environments of unstable background because of winds, and illuminations changes. The results show that our approach is more robust to background noises and performs better than previous methods.

• 대한원격탐사학회지
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• 제36권4호
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• pp.535-544
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• 2020

In synthetic aperture radar (SAR) based ship detection application, false alarms frequently occur due to various noises caused by the radar imaging process. Among them, radio frequency interference (RFI) and azimuth smearing produce substantial false alarms; the latter also yields longer length estimation of ships than the true length. These two noises are prominent at cross-polarization and relatively weak at co-polarization. However, in general, the cross-polarization data are suitable for ship detection, because the radar backscatter from background sea surface is much less in comparison with the co-polarization backscatter, i.e., higher ship-sea image contrast. In order to improve the ship detection accuracy further, the RFI and azimuth smearing need to be mitigated. In the present letter, Sentinel-1 VV- and VH-polarization intensity data are used to show a novel technique of removing these noises. In this method, median image intensities of noises and background sea surface are calculated to yield arithmetic tendency. A band-math formula is then designed to replace the intensities of noise pixels in VH-polarization with adjusted VV-polarization intensity pixels that are less affected by the noises. To verify the proposed method, the adaptive threshold method (ATM) with a sliding window was used for ship detection, and the results showed that the 74.39% of RFI false alarms are removed and 92.27% false alarms of azimuth smearing are removed.

• 수산해양기술연구
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• 제58권3호
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• pp.223-229
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• 2022

This study investigated the methods of effectively removing noises in the acoustic data collected from the cold water zone of the East Sea, and converted that data into NASC values for comparison and analysis. First, the noises accompanying the acoustic data were divided into background noise, impulse noise, transient noise and attenuated signals according to the pattern characteristics. Then, the NASC values before and after noise removal were compared. As a result, the background noises were found to show the highest difference of 6,946 times in the NASC values before and after removal. The attenuated signals showed that the NASC values were higher after the removal.