• 반도체디스플레이기술학회지
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• 제10권1호
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Annals of Clinical Neurophysiology
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• 제3권1호
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• pp.26-30
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• 2001

Purpose : Eyeball movement is one of the main artifacts in EEG. A new approach to the removal of these artifacts is presented using independent component analysis(ICA). This technique is a signal-processing algorithm to separate independent sources from unknown mixed signals. This study was performed to show that ICA is a useful method for the separation of EEG components with little data deformity. Methods : 12 sets of 10 sec digital EEG data including eye opening and closure were obtained using international 10~20 system scalp electrodes. ICA with 18 tracings of double banana bipolar montage was performed. Among obtained 18 independent components, two components, which were thought to be eyeball movements were removed. Other 16 components were reconstructed into original bipolar montage. Power spectral analysis of EEGs before and after ICA was done and compared statistically. Total 12 pairs of data were compared by visual inspection and relative power comparison. Results : Waveforms of each pair looked alike by visual inspection. Means of relative power before and after ICA were 29.16% vs. 28.27%, 12.12% vs. 12.41%, 10.55% vs. 10.52%, and 19.33% vs. 18. 33% for alpha, beta, theta, and delta, respectively. These values were statistically same before and after ICA. Conclusions : We found little data deformity after ICA and it was possible to isolate eyeball movements in EEG recordings. Many other components of EEG could be selectively separated using ICA.

• 대한인간공학회지
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• 제10권2호
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• pp.31-42
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• 1991

To understand the shape of the neck in a view of garment planning, principal component analysis has been appliedto the measurement of the neck. The neck surface development and the cross sections of the neck have been observed. The materials consist of the body mearsurements, the neck surface developments and the cross sec- tions of the necks of a total of 108 korean woman students. The difference between the right side and the left side of the neck has not been reconginiged. But the differenece among the height of the front neck point, that of the side neck point and that of the back neck point has been recognized. 2. The initial 41 items have been found having variety and duplication. So two criteria have been made to solve those problems and the selection of 34 items have been made by each criterion. 3. 43 and 34 items have been compared by means of accumulative ratios of contribution and of clearness within the meaning of principal component. As a result, 34 measurement items have been further anylysis. 4. As a result of principal component analysis on the 34 items, the four principal components have been found obtaines and inter-preted. The four principal components are 1) the thick of the neck, 2) the front neck-line on the waist basic pattern, basic pattern, 3) the shape of the neck surface development, and 4) the back neck-line on the waist basic pattern. 5. According to the graphic informations concerning these principal components, the meaning of these four principal components has been grasped on the visual. As a result, there is a large individual difference in the shape of neck.

• 한국신뢰성학회지:신뢰성응용연구
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• 제15권4호
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• pp.233-240
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• 2015

We analyse reliability of multi-state UH-60 helicopter hydraulic pump system with a multi-functional standby component using Markov analysis method. The system consists of seven components: 2 main pumps, 1 standby pump, 2 primary servos, and 2 tail rotor servos. The standby pump can take over when one more than components fail. Therefore the standby pump is multi-functional standby component. The system has four states: good, deteriorated, dangerous, and failed. The components have 2 states: working and failed. We assume the system is unrepairable when the components fail. We estimate failure distributions and rates using collected failure time data in field. And we classify multi-state of the system according to emergency procedure of UH-60A student handout. We obtain the reliabilities of multi-state system using Visual Basic program because the differential equations is extremely complicated and tedious to solve.

• 한국컴퓨터정보학회논문지
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• 제16권4호
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• pp.15-22
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• 2011

주성분 분석(PCA)은 데이터의 차원을 줄이면서 최대의 데이터 변이를 보존하는 기법으로 차원 축소나 특징 추출을 위해 널리 사용되고 있다. 하지만 PCA는 잡음에 민감하며 가우스 분포에 대하여만 유효하다는 단점이 있다. 잡음 민감성의 개선을 위해 다양한 방법이 제시되었고 그 중 퍼지 소속도를 이용한 반복적 최적화 기법인 RF-PCA2가 다른 방법에 비해 우수한 성능을 보였다. 하지만 RF-PCA2는 가우스 분포에만 사용할 수 있는 선형 알고리듬이라는 한계가 있다. 이 논문에서는 RF-PCA2와 커널 주성분 분석(kernel PCA, K-PCA)을 결합하여 가우스 분포 이외의 분포들도 다룰 수 있는 비선형 알고리듬인 improved robust kernel fuzzy PCA (RKF-PCA2)를 제안한다. RKF-PCA2는 RF-PCA2 알고리듬의 잡음 강건성과K-PCA의비선형성을 통해 기존알고리듬에 비해 잡음민감성이 적으며 가우스분포 한계를 효과적으로 극복할 수 있다. 이러한 사실은 실험 결과를 통해 확인할 수 있다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 춘계 종합학술대회 논문집
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• pp.437-442
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• 2005

본 연구에서는 칼라정보와 주성분분석법(principal component analysis : PCA)를 이용한 차량 번호판 인식시스템을 구성하였다. 먼저 입력된 차량 영상에서 번호판의 형태적 특징과 녹색 칼라 정보를 이용하여 번호판 영역을 추출하였으며, 추출된 번호판내의 문자 및 숫자의 위치적 특징을 이용하여 번호판의 종류(구형, 신형, 최신형)를 구분하였다. 이렇게 추출되고 구분된 번호판은 문자의 상대적 위치정보와 수평 및 수직 투영 정보를 함께 이용하여 각각의 문자영역을 분리 추출하였다. 추출된 문자영역은 주성분분석법을 이용하여 고유벡터를 추출한 후 문자 인식에 사용하였다. 본 논문의 실험과정에서는 다양한 시간대 환경에서 촬영된 주행 중인 자동차 320대의 자가용 차량영상에 대하여 실험하였으며 높은 번호판 추출률과 번호판종류 구분률 그리고 문자 인식률을 얻을 수 있었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.407-410
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• 2003

We propose a new logo watermark scheme for digital images which embed a watermark by modifying middle-frequency sub-bands of wavelet transform. Independent component analysis (ICA) is introduced to authenticate and copyright protect multimedia products by extracting the watermark. To exploit the Human visual system (HVS) and the robustness, a perceptual model is applied with a stochastic approach based on noise visibility function (NVF) for adaptive watermarking algorithm. Experimental results demonstrated that the watermark is perfectly extracted by ICA technique with excellent invisibility, robust against various image and digital processing operators, and almost all compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal components analysis (PCA) based compression.

• The Journal of the Acoustical Society of Korea
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• 제25권3E호
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• pp.89-94
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• 2006

For audio indexing and targeted search of specific audio or corresponding visual contents, the MPEG-7 standard has adopted a sound classification framework, in which dimension-reduced Audio Spectrum Projection (ASP) features are used to train continuous hidden Markov models (HMMs) for classification of various sounds. The MPEG-7 employs Principal Component Analysis (PCA) or Independent Component Analysis (ICA) for the dimensional reduction. Other well-established techniques include Non-negative Matrix Factorization (NMF), Linear Discriminant Analysis (LDA) and Discrete Cosine Transformation (DCT). In this paper we compare the performance of different dimensional reduction methods with Gaussian mixture models (GMMs) and HMMs in the classifying video sound clips.

• 보존과학회지
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• 제35권1호
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• pp.91-98
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• 2019

The fragments of a wall painting excavated from among the historical remains of Jeseoksa Temple in Iksan. The extent of the damage to the fragments was examined and an analysis of the components of the pigment was conducted. The results of the component analysis of the pigment confirmed that the white pigment consisted of alkali feldspar and mullite. Although the results of the visual inspection revealed differences in color in the red and black pigments, the main component of the two colors was confirmed to be iron oxide. Red and black pigments are found at the same position. Although differences of color is obvious, those are identified as hematite and magnetite of oxidized steel's affiliation. It is judged that Differences of ingredients happened by external environment's factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4502-4512
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• 2014

This article presents a reformulation of the Grey Edge framework for colour constancy. Colour constancy is the ability of a visual system to perceive objects' colours independently of their scenes' illuminants. Colour constancy algorithms try to estimate the colour of an illuminant from image values. This estimation can later be used to correct the image as though it were taken under a white illuminant. The modification presented allows the framework to incorporate image-specific filters instead of the commonly used edge detectors. A colour constancy algorithm is proposed using PCA and FastICA linear component analyses methods for the construction of such filters. The results show that the proposed method improves the accuracies of the Grey Edge framework algorithms whilst on the other hand, achieving comparable accuracies with the state-of-the-art methods, but improving their time efficiencies.