• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1673-1678
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• 2016

In the area of the speech recognition processing, background noises are caused the incorrect response to the speech input, therefore the speech recognition rates are decreased by the background noises. Accordingly, a more high level noise processing techniques are required since these kinds of noise countermeasures are not simple. Therefore, this paper proposes an algorithm to distinguish between the stationary background noises or non-stationary background noises and the speech signal having short time duration in the noisy environments. The proposed algorithm uses the characteristic parameter of the improved speech signal as an important measure in order to distinguish different types of the background noises and the speech signals. Next, this algorithm estimates various kinds of the background noises using a multi-layer perceptron neural network. In this experiment, it was experimentally clear the estimation of the background noises and the speech signals.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.106-110
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• 2004

The noise characteristics of the submarines and vessels are composed of tonal signals and background noises. Tonal signals are from the revolution of the motors or engines, and background noises are from the generation and disappearing of the bubbles around the vessels. We analyze the noises from maneuvering underwater vessels with ATW algorithm. We design broadband asymptotic noise generator using Hilbert transform and design the system which can generate asymptotic noise with sum of generated background noise and synthesized tonal signals. This system can be used as a cheating system from the torpedo shacks.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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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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• v.3 no.2
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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.

• Phonetics and Speech Sciences
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• v.7 no.1
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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.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.133-147
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• 2001

This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.112-119
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• 2000

A two-color infrared (IR) seeker employs two detection-bands for efficient target tracking under countermeasures and background noises. This paper describes a study on the detection-band selections for the two-color seeker. To select the detection-bands, we analysis infrared radiation characteristics of a target, a flare, and background noises and then other characteristics closely related with the received power, such as the atmospheric transmission, acquisition range, background noise effect, and signal-to-noises. The analysis shows that the pertinent bands of two-color IR seeker are 3 um~5 um for target detection and 1.5 um~l.7 um for counter-countermeasures. The results of our study will play a significant role in the further study of two-color seekers.

• Smart Media Journal
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• v.5 no.1
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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.

• Korean Journal of Remote Sensing
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• v.36 no.4
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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.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.3
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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.