• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.515-519
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• 2005

Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algoritms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algoritm is increased. So in this paper we proposed the simple algorithm using modified AMDF that detects global minimum valley point as pitch period of speech signal and compared existing methods with it through simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1019-1022
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• 2005

As recent information communication technology is rapidly developed, a lot of researches related to speech signal processing have been processed. So pitch period is applied as important factor to many application fields such as speech recognition, speaker identification, speech analysis and synthesis. Therefore, many algorithms related to pitch detection have been proposed in time domain and frequency domain and AMDF(average magnitude difference function) which is one of pitch detection algorithms in time domain chooses time interval from valley to valley as pitch period. But, in selection of valley point to detect pitch period, complexity of the algorithm is increased. So in this paper we proposed pitch detection algorithm using rotation transform of AMDF, that taking the global minimum valley point as pitch period and established a threshold about the phoneme in beginning portion, to exclude pitch period selection. and compared existing methods with proposed method through simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.23-28
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• 2006

Pitch period that is a important factor in speech signal processing is used in various applications such as speech recognition, speaker identification, speech analysis and synthesis. So many pitch detection algorithms have been studied until now. AMDF which is one of pitch period detection algorithms chooses the time interval from valley point to valley point as pitch period. In selection of valley point to detect pitch period, complexity of the algorithm is increased. So in this paper we proposed the simple algorithm using rotation transform of AMDF that detects global minimum valley point as pitch period of speech signal and compared it with existing methods through simulation.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.178-183
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• 2006

As a lot of researches on the speech signal processing are performed due to the recent rapid development of the information-communication technology. the pitch period is used as an important element to various speech signal application fields such as the speech recognition. speaker identification. speech analysis. or speech synthesis. A variety of algorithms for the time and the frequency domains related with such pitch period detection have been suggested. One of the pitch detection algorithms for the time domain. AMDF (average magnitude difference function) uses distance between two valley points as the calculated pitch period. However, it has a problem that the algorithm becomes complex in selecting the valley points for the pitch period detection. Therefore, in this paper we proposed the modified AMDF(M-AMDF) algorithm which recognizes the entire minimum valley points as the pitch period of the speech signal by using the rotation transform of AMDF. In addition, a threshold is set to the beginning portion of speech so that it can be used as the selection criteria for the pitch period. Moreover the proposed algorithm is compared with the conventional ones by means of the simulation, and presents better properties than others.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.187-192
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• 2009

In this paper the extended algorithm of valley energy was proposed In order to detect the robust features of the face The proposed energy had the variable type without the constant size of valley mask for measuring the gray value among pixels By accumulating the results generated by the various masks the information of valley energy was so diversified. Then the robust energy which is independent of the environments was maded. The various experiments proved that The proposed method showed the detection rate of 98 percentage in the features of the face region.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.481-484
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• 2006

Pitch period detection algorithms are applied to various speech signal processing fields such as speech recognition, speaker identification, speech analysis and synthesis. Furthermore, many pitch detection algorithms of time and frequency domain have been studied until now. AMDF(average magnitude difference function) ,which is one of pitch period detection algorithms, chooses a time interval from the valley point to the valley point as the pitch period. AMDF has a fast computation capacity, but in selection of valley point to detect pitch period, complexity of the algorithm is increased. In order to apply pitch period detection algorithms to the real world, they have robust prosperities against generated noise in the subway environment etc. In this paper we proposed the modified AMDF algorithm which detects the global minimum valley point as the pitch period of speech signals and used speech signals of noisy environments as test signals.

• Food Science and Biotechnology
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• v.17 no.4
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• pp.846-849
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• 2008

This study employed high performance liquid chromatography (HPLC) coupled to an on-line $ABTS^+$ radical scavenging detection (RSD) system along with HPLC-electro spin impact/mass spectrometry (ESI/MS), to rapidly determine and identify antioxidant compounds occurring in blueberry extract. The extract was separated by HPLC, and then the radical scavenging activities of the separated compounds were evaluated by the on-line coupled $ABTS^+$-RSD system. The negative peaks of the $ABTS^+$-RSD system, which indicates the presence of antioxidant activity, were monitored by measuring the decrease in absorbance at 734 nm. The active components in the blueberry extract were identified by HPLC-ESI/MS using their MS spectra and retention times. According to the data acquired from the on-line HPLC-$ABTS^+$-based assay and HPLC-ESI/MS systems, the antioxidant compounds detected in the blueberry extract were identified as chlorogenic acid and 11 anthocyanins.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.46-51
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• 2002

In this paper, I proposed a eyebrow detection algorithm in human face, that is important element in facial recognition. The proposed algorithm consists of four processes: face region detection using color region segmentation. eye detection by template matching, eyebrow candidate region detection in detected eye region, and eyebrow detection by thresholding using the modified histogram that gets luminance value in the candidate region. The test results show that the proposed algorithm can detect eyebrow region very effectively in facial image.

• Journal of Sensor Science and Technology
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• v.14 no.1
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• pp.28-32
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• 2005

In this paper, a CMOS integrated detection circuit for capacitive type fingerprint sensor signal processing is described. We designed a detection circuit of charge-sharing sensing scheme. The proposed detection circuit increases the voltage difference between a ridge and valley. The test chip is composed of $160{\times}192$ array sensing cells (12 by $12.7{\;}mm^{2}$). The chip was fabricated on a 0.35 m standard CMOS process. Measured difference voltage between a ridge and valley was 0.95 V.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.301-304
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• 2011

This paper describes the possibility of a low-power, high-resolution fingerprint sensor chip. A modified capacitive detection circuit of charge sharing scheme is proposed, which reduces the static power dissipation and increases the voltage difference between a ridge and valley more than conventional circuit. The detection circuit is designed and simulated in 3.3V, 0.35${\mu}$m standard CMOS process, 40MHz condition. The result shows about 27% power dissipation reduction and 90% improvement of difference between a ridge and valley sensing voltage. The proposed circuit is more stable and effective than a typical circuit.