• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2363-2371
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• 2015

In this paper, we propose a new feature matching algorithm which is robust to the viewpoint change by using the FAST(Features from Accelerated Segment Test) feature detector and the SIFT(Scale Invariant Feature Transform) feature descriptor. The original FAST algorithm unnecessarily results in many feature points along the edges in the image. To solve this problem, we apply the principal curvatures for refining it. We use the SIFT descriptor to describe the extracted feature points and calculate the homography matrix through the RANSAC(RANdom SAmple Consensus) with the matching pairs obtained from the two different viewpoint images. To make feature matching robust to the viewpoint change, we classify the matching pairs by calculating the Euclidean distance between the transformed coordinates by the homography transformation with feature points in the reference image and the coordinates of the feature points in the different viewpoint image. Through the experimental results, it is shown that the proposed algorithm has better performance than the conventional feature matching algorithms even though it has much less computational load.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1614-1614
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• 2001

The sweetness (。Bix) of fruit is the main quality factor contributing to the fruit taste. The brix of the apple fruit can be measured non-destructively by near infrared (NIR) spectroscopy, allowing the sweetness grading of individual apple fruit. However, the fruit quality is influenced by various factors such as growing location, producing year, variety and harvest time etc., accordingly the robust NIR calibration is required. In this experimental results are presented the influence of two variations such as growing location and producing year of apple fruit in establishing of calibrations for sweetness, and developed a stable and highly accurate calibration. Apple fruit (Fuji) was collected every year from 1995 to 1997 in 3 different growing locations (Andong, Youngchun and Chungsong) of Kyungpook in Korea. NIR reflectance spectra of apple fruit were scanned in wavelength range of 1100∼2500nm using an InfraAlyzer 500C (Bran+Luebbe) with halogen lamp and PbS detector. The multiple linear regression and stepwise was carried out between the NIR raw spectra and the brix measured by refractometer to select the best regression equations. The calibration models by each growing district were well predicted to dependent sample set, but poorly predicted to independent sample set. Combined calibration model using data of three growing districts predicted reasonable well to a population set drawn from all growing districts(SEP = 0.69%, Bias=-0.075). The calibration models by each harvest year were not transferable across harvest year, however a combined calibration model using data of three harvest years was sufficiently robust to predict each sample sets(SEP = 0.53%, Bias = 0.004).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1631-1637
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• 2019

In this paper, we propose a low-complexity robust maximum likelihood (ML) receiver for generalized spatial modulation. The proposed receiver performs the transmit antenna partition to lower the computational loads. After we divide the transmit antenna combinations into two parts, one of which is "the likely TAC part," and the other of which is "the unlikely TAC part", based on the minimum mean square error (MMSE) filtering output. We first perform the maximum likelihood detection only in the likely TAC part. Then we evaluate the reliability of the solution found in the first search, and based its reliability we decide whether we continue the search in the unlikely TAC part. This partitioned search strategy maintains the performance of the conventional robust maximum likelihood receiver and simultaneously lowers computational loads. Through simulation, we found that our newly-proposed receiver achieves considerable gains over the conventional robust ML detector in terms of the computational loads while providing almost the same performance.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.503-505
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• 1999

경계선 검출은 컴퓨터를 이용한 영상인식의 첫 단계로서, 인식의 성능에 큰 영향을 미치는 중요한 기술이다. 여러 가지 경계선 검출 기술들이 존재하지만, 이들은 모두 주어진 영사에 잡음이 존재하지 않거나 존재의 정도가 미약한 경우를 가정하여 개발되었다. 한편, 잡음이 심하게 삽입된 경우에는 경계선 검출기 적용 이전에 잡음제거 필터를 사용할 수 있다. 그러나 주어진 영상에 잡음이 존재하는지를 어떻게 컴퓨터 스스로 판단할 것인가\ulcorner 본 연구에서는 주어진 영상에 대하여 잡음의 존재 여부와 잡음의 정도 여부에 상관없이, 굳건한 경계선 검출 능력을 보이는 경계선 검출기를 개발하였다. 이를 위하여 이중 필터를 사용하였는데, 그 중 하나는 일반적으로 많이 사용되는 가우시안 필터이고, 다른 하나는 본 연구진에 의하여 개발된 웨이블릿 기반 필터이다. 실험결과, 본 논문의 경계선 검출기는 잡음의 정도에 크게 구애받지 않는 일정한 성능을 보여주었다.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2589-2592
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• 2003

In this paper, a robust mixed H$_2$/H$\_$$\infty$/ output feedback control method is applied to the design of loop filter for PLL carrier phase tracking. The proposed method successfully copes with large S-curve slope uncertainty and a significant decision delay in the closed-loop that may exist In modern receivers due to a convolutional decoder or an equalizer. The objective is to design an output feedback controller which minimizes the H$_2$performance while satisfying the H$\_$$\infty$/ performance to guarantee the gain margin and phase margin for linear time invariant(LTI) polytopic uncertain systems. LMIs based approach is given to solve this problem. We can verify the H$\_$$\infty$/ performance satisfaction and minimize the phase detector error through the simulation result.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.111-117
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• 2009

In this paper, a new speech endpoint detector in noisy environment is proposed. According to the previous research, the energy feature in the speech region is easily distinguished from that in the speech absent region. In conventional method, the endpoint can be found by applying the edge detection filter that finds the abrupt changing point in feature domain. However, since the frame energy feature is unstable in noisy environment, the accurate edge detection is not possible. Therefore, in this paper, the novel feature extraction method based on spectrum envelop pattern is proposed. Then, the edge detection filter is applied to the proposed feature for detection of the endpoint. The experiments are performed in the car noise environment and a substantial improvement was obtained over the conventional method.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.6
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• pp.380-389
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• 2006

A new laser-based ultrasonic receiver that is based on multi-channel interferometry is shown to be well suited for robust and sensitive detection of ultrasound in industrial environment. The proposed architecture combines random-quadrature detection with detector arrays and parallel multi-speckle processing. The high sensitivity is reached, thanks to the random phase distribution of laser speckle caused by surface roughness. High-density parallel signal processing is achieved by using a simple demodulation technique based on signal rectification. This simple detection scheme is also demonstrated for rejection of the laser intensity noise, making possible the use of lower cost laser without reduction in performances. Results demonstrating this new principle of operation and its performances are presented.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.71-74
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• 2003

The signal processing algorithm for a PSD(Position Sensitive Detector) using amplitude modulation/demodulation is addressed in this paper. Dark currents and external noises such as daylight and fluorescent lights are eliminated by using amplitude modulation/demodulation and a low pass filter. The proposed amplitude modulation/demodulation method for a PSD sensor is compared with pulse amplitude modulation method. The proposed amplitude modulation is proved to be more accurate and robust than PAM method by analysis and experiments. Multiple measurements using one PSD sensor by amplitude modulation/demodulation is also addressed. The Power variation of light source is compensated by normalization process using a divider.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.124-132
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• 2003

We propose a new method for speech/non-speech classifiers based on concepts of the adaptive boosting (AdaBoost) algorithm in order to detect speech for robust speech recognition. The method uses a combination of simple base classifiers through the AdaBoost algorithm and a set of optimized speech features combined with spectral subtraction. The key benefits of this method are the simple implementation, low computational complexity and the avoidance of the over-fitting problem. We checked the validity of the method by comparing its performance with the speech/non-speech classifier used in a standard voice activity detector. For speech recognition purpose, additional performance improvements were achieved by the adoption of new features including speech band energies and MFCC-based spectral distortion. For the same false alarm rate, the method reduced 20-50% of miss errors.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.603-605
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• 1999

본 논문은 통계적 Regression방법인 Alternating Conditional Expectation(ACE) 방법을 적용하여 다중계측기를 이용한 공간 변수의 분포에 대한 추정 혹은 재구성 문제를 분석하는 방법을 제시하고 있다. 한다. 계측기 설치 비용 및 설치 위치의 한계로 인해 완벽하게 이루어지기 힘든 공간 변수의 연속적인 분포 추정은 공정 시스템이나 안전성 관련 변수의 감시분야에 많이 응용되고 있다. 본 논문은 계측기 추가에 따르는 비용을 줄이거나 동일한 수의 계측기로 측정오차를 감소시킬 목적으로 가상계측기의 개념을 도입하고 이를 적용하기 위한 통계적 추정 방법론을 기술하고 있다. 수치모사를 통한 분석결과 본 방법은 비선형성이 큰 변수분포에 대해서도 Robust한 결과를 주는 것을 확인하였다.