• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.58-65
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• 2009

The paper identifies noise characteristics of a nonliner image sensor model which reflects a saturation effect of each detector pixel and extends the result to estimate an image SNR (Signla-to-Noise Ratio) distribution over all the pixels in a detector. In particular, nonlinearity of a pixel is studied from two perspectives of including asymmetry of a noise PDF (Probability Distribution Function) and enhancing a pixel SNR value, in comparison to a linear model. It is noted that the proposed image SNR distribution function is useful to effectively select new optimal operation parameter values: an integration time and an pixel-summing number, even after a launch campaign, assuming sensor gain degradation in orbit or inevitable modification of some operation parameter values due to space contingency.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.773-782
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• 2018

A frequency-locked loop(FLL) is a negative-feedback system that uses a frequency detector to improve the phase noise of a voltage-controlled oscillator(VCO). In this work, a theoretical analysis of the phase noise of a VCO in an FLL is presented. The analysis shows that the phase noise of the VCO follows the phase noise determined by the frequency detector and the loop filter within the FLL loop bandwidth, while the phase noise of the VCO appears outside the loop bandwidth. Therefore, it is possible to design an FLL that minimizes the phase noise of the VCO based on the theoretical analysis results. The theoretical phase noise results were verified through experiments.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.550-555
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• 2007

초음파 영상은 초음파 펄스를 이용하여 반사파를 수신하여 진단에 필요한 영상을 구성하는데 신호가 약해 질 경우 잡음이 발생하며 미세한 명암도 차이 등에 의해 분석과정에서 육안으로 인지하고 진단하는데 어려움이 있다. 특히 근골격계 검사를 위한 초음파 영상에서 근육 영역의 진단에 어려움을 준다. 따라서 본 논문에서는 초음파 영상에서 영상처리 기법을 이용하여 근육 영역을 검출할 수 있는 방법을 제안한다. 초음파 영상에서의 근육 영역검출은 피하지방층과 기타 영역 그리고 근육을 둘러싸고 있는 근육막 후보 영역을 검출한 후, 위치 정보와 형태학적 특징을 이용하여 최종적으로 근육막 내부 영역인 근육 영역을 검출한다. 제안된 방법의 근육막 후보 영역의 검출 과정은 개선된 히스토그램 스트레칭과 Mutiple연산으로 대비 차를 향상시키고 반복 이진화 기법을 적용한 후, 잡음에 의해 손실되거나 끊어진 근육막 영역을 거리 및 방향 분석을 이용하여 연결한 후에 근육막 후보 영역을 검출한다. 검출된 근육막 후보 영역의 형태학적 특징과 위치 정보를 이용하여 피하지방층과 기타 영역을 분류 한 후, 최종적으로 근육 영역을 검출한다. 실제 초음파 영상을 대상으로 제안된 근육 검출 방법을 적용하여 검출된 근육 영역과 전문의가 분석한 근육 영역을 비교한 결과, 제안된 근육 검출 방법이 전문의가 육안으로 분석한 근육영역과 근접하게 검출되어 본 논문에서 제안한 근육 영역 검출 방법이 효율적임을 확인할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.5
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• pp.21-27
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• 2008

Despite recent studies on development of pulse diagnosis systems and needs for commercializing them, the reproducibility is one of the most controversial issues as ever. Because the pulse pressure value, which is one of the important parameters to evaluate reproducibility, is very vulnerable to moving artifacts, the reproducibility can not be obtained easily. In this paper, we suggested a moving artefacts detection system for a pulse diagnosis system so that a pulse diagnosis system can be robust to theses kinds of artefacts by excluding the contaminated parts from the pulse wave signal to be analyzed. This moving artifacts detection system was designed to consist of a three-axis accelerometer, an electromyography amplifier and a two-axis tilt sensor. To assess the suitability of the system, we examined the characteristics of each sensor's output signals with regard to the three specific motions such as extension, flexion and rotation. And, we also examined the each sensor's response to the high-frequency and low-frequency moving artifacts while the pulse wave signal was acquired from a pressure sensor for the pulse diagnosis. From these results, we could find that the response to subject's motions would be reflected in electromyography signal first, in accelerometer signals and in tilt sensor sequently. And, the facts that a stable pulse wave can be acquired in two seconds after high frequency or low frequency motions ended, were also found. Consequently, based on these findings, we set up some rules on the moving artifacts detection and designed an algorithm which is fit for our moving artifacts detection system.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.73-75
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• 2009

본 논문은 영상 처리에 의해 광학렌즈의 먼지 및 이물질의 유무를 검출하기 위한 방법을 제안한다. 현재 사용되고 있는 비접촉 검사용 비젼 시스템은 마스크 기법을 활용하여 기준 영상에 비해 어느 정도의 잡음이 있는지를 검사한다. 그러나 조명의 정도, 반사 및 이물질의 유형에 따라 검출하기가 어렵다. 이를 해결하기 위해 파란색 LED 광원을 수평축에 설치하여 양각 부분의 에지들을 더욱 강조하는 시스템을 구현하였다. 이물질 검출은 간단한 소벨 에지 마스크를 사용하고 이물질의 크기에 따라 먼지 및 이물질에 대한 판단을 결정하였다. 크기 및 색상이 틀린 렌즈를 사용하여 실험한 결과 일반 영상에서 검출한 것보다 파란색 LED 광원과 영상처리에 의해 잡음 및 이물질을 강건하게 검출하여 렌즈의 자동 검사용 로봇 비젼 시스템에 적용이 가능하다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.57-64
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• 1999

In this paper, we investigated the robust endpoint detection algorithm in noisy environment. A new feature parameter based on a discrete wavelet transform is proposed for word boundary detection of isolated utterances. The sum of standard deviation of wavelet coefficients in the third coarse and weighted first detailed scale is defined as a new feature parameter for endpoint detection. We then developed a new and robust endpoint detection algorithm using the feature found in the wavelet domain. For the performance evaluation, we evaluated the detection accuracy and the average recognition error rate due to endpoint detection in an HMM-based recognition system across several signal-to-noise ratios and noise conditions.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.839-842
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• 2009

It is used to differential image for moving object detection in general. But it is difficult to detect the accurate detection which uses differential image between frames. In this paper, the proposed method overcome the noise that is generated by camera, grabber card, or weather condition. It extract to moving big object such as human or vehicle. The proposed method process morphological filtering and binary for the image with noise, reduce error. We are expect to apply to a real-time moving object detection system at fog condition, pass the limit of the object detection method using the differential image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1105-1116
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• 2008

Cognitive radio is one of the most effective techniques to improve the spectrum utilization efficiency. To implement the cognitive radio, spectrum sensing is considered as the key functionality because only counting on it, can the secondary users identify the spectrum holes and utilize them efficiently without causing interference to primary users. Generally, there are several spectrum sensing methods; the most common and simplest method is energy detection. However, the conventional energy detection has some disadvantages, which are caused by noise, especially, uncertain noise power leads to degradation of energy detector. In this paper, to solve this problem, we proposed sliding window-based energy detection method which can devide the frequency band of primary signal and noise using sliding window to estimate the power of primary user without the noise effect and achieve the better performance. It can calculate the energy of primary user only and can detect the primary signal. The simulation result shows that our proposed method outperforms conventional one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1635-1644
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• 1993

In this paper, we examine the statistical characteristics of edge enhancing filters and their efficacy as preprocessing operator before edge detection. In particular, edge enhancing filters called the Comparison and Selection(CS), Hachimura-kuwahara(HK), and Selective Average(SA) filters are considered. These filters can reduce noise while producing step-type edges, thus seem to be effective for preprocessing noisy images prior to applying edge detecors. The ability of edge enhancing filters to suppress white Gaussian noise and the error probabilities occured during the edge detection following SA prefiltering are evaluated statistically through numerical analysis. The effect of prefiltering on edge detection is assessed by applying the edge enhancing fitters to a noise image degraded by additive white noise prior to applying the Sobel operator and the Laplacian of Gaussian( LoG ) operator, respectively. It is shown that the edge enhancing filters tend to produce ideal step-type edges while reducing the noise reasonably well, and the use of edge enhancing filters prior to edge detection can improve the performance of subsequent edge detector.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.483-490
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• 2009

In this paper, we develop a speech interface that has acoustic echo cancelling and barge-in functionalities in the car environment. In the echo canceller, DT (Double-Talk) detection algorithm using the correlation coefficients between reference and desired signals can make DT detection errors often in the background noise. We reduce the DT detection errors by using the average power of noise and echo estimated from the input signal. In addition, to make it possible for drivers to give speech command to the system by interrupting the speaker output, barge-in functionality is implemented with the combination of DT detection and appropriate gain control of the speaker output. Through the computer simulation with the assumed car environment and experiment in the real laboratory environment, implemented speech interface has shown good performance in removing acoustic echo signals in the noisy environment with proper operation of barge-in functionality.