• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.8-14
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• 2007

X-ray digital tomosynthesis is widely used in the nondestructive testing and evaluation, especially for the printed circuit boards (PCBs). In this study, we propose a simple method to reduce the blur artefact, frequently claimed in the conventional digital tomosynthesis based on SAA (shift-and-add) algorithm, and thus restore the image sharpness. The proposed method is basically based on the SAA, but has a correction procedure by finding blur artefacts from the forward-and back-projection for the firstly obtained, manipulated backprojection data. The manipulation is the replacement of the original data at the POI (plane-of-interest) by zeros. This method has been compared with the conventional SAA algorithm using the experimental measurements and Monte Carlo simulation for the designed PCB phantom. The comparison showed a much enhancement of sharpness in the images obtained from the proposed method.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.267-270
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• 1999

In this paper, a new method to reduce the size of ROM in the direct digital frequency synthesizer (DDFS) is proposed. In the case that ROM is used for sinusoidal value calculation, reducing the size of ROM is significant. So the power consumption is affected mostly by its bit width. In the proposed method, the ROM bit width is reduced by 1 bit using the phase subtraction and the approximation. The spurious level is better than 80㏈c and the power consumption estimated is 510㎼/MHz.

• 대한치주과학회:학술대회논문집
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• 2004.11a
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• pp.119-120
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• 2004

• 대한치주과학회:학술대회논문집
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• 2001.12a
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• pp.87-88
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• 2001

• Journal of Periodontal and Implant Science
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• v.21 no.2
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• pp.188.1-188.1
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• 1991

• Journal of Periodontal and Implant Science
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• v.20 no.2
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• pp.158-158
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• 1990

• Proceedings of the KSMRM Conference
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• 2005.09a
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• pp.31-31
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• 2005

• 대한치주과학회:학술대회논문집
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• 2000.11a
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• pp.130-131
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• 2000

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.133-139
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• 2004

In this paper. we propose a medical image processing method for detection of periodontal disease by geometric analysis on dental digital radiography. This paper proposes the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by image processing technique, that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the geometric features in target images. Therefore, we use these methods because they give accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.732-743
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• 2007

Background noise is one of the major complaints of not only hearing impaired persons but also normal listeners. This paper describes the results of two experiments in which speech recognition performance was determined for listeners with normal hearing and sensorineural hearing loss in noise environment. First, we compared speech enhancement algorithms by evaluation speech recognition ability in various speech-to-noise ratios and types of noise. Next, speech enhancement algorithms by reducing background noise were presented and evaluated to improve speech intelligibility for sensorineural hearing impairment listeners. We tested three noise reduction methods using single-microphone, such as spectrum subtraction and companding, Wiener filter method, and maximum likelihood envelop estimation. Their responses in background noise were investigated and compared with those by the speech enhancement algorithm that presented in this paper. The methods improved speech recognition test score for the sensorineural hearing impaired listeners, but not for normal listeners. The results suggest the speech enhancement algorithm with the loudness compression can improve speech intelligibility for listeners with sensorineural hearing loss.