• Journal of KIISE
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• v.41 no.9
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• pp.666-673
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• 2014

This paper proposes a scalable face recognition method for unconstrained face databases, and shows a simple experimental result. Existing face recognition research usually has focused on improving the recognition rate in a constrained environment where illumination, face alignment, facial expression, and background is controlled. Therefore, it cannot be applied in unconstrained face databases. The proposed system is face feature extraction algorithm for unconstrained face recognition. First of all, we extract the area that represent the important features(landmarks) in the face, like the eyes, nose, and mouth. Each landmark is represented by a high-dimensional LBP(Local Binary Pattern) histogram feature vector. The multi-scale LBP histogram vector corresponding to a single landmark, becomes a low-dimensional face feature vector through the feature reduction process, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis). We use the Rank acquisition method and Precision at k(p@k) performance verification method for verifying the face recognition performance of the low-dimensional face feature by the proposed algorithm. To generate the experimental results of face recognition we used the FERET, LFW and PubFig83 database. The face recognition system using the proposed algorithm showed a better classification performance over the existing methods.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.438-456
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• 2010

Iris recognition uses a unique iris pattern of user to identify person. In order to enhance the performance of iris recognition, it is reported that the diameter of iris region should be greater than 200 pixels in the captured iris image. So, the previous iris system used zoom lens camera, which can increase the size and cost of system. To overcome these problems, we propose a new method of enhancing the accuracy of iris recognition on low-resolution iris images which are captured without a zoom lens. This research is novel in the following two ways compared to previous works. First, this research is the first one to analyze the performance degradation of iris recognition according to the decrease of the image resolution by excluding other factors such as image blurring and the occlusion of eyelid and eyelash. Second, in order to restore a high-resolution iris image from single low-resolution one, we propose a new method based on multiple multi-layered perceptrons (MLPs) which are trained according to the edge direction of iris patterns. From that, the accuracy of iris recognition with the restored images was much enhanced. Experimental results showed that when the iris images down-sampled by 6% compared to the original image were restored into the high resolution ones by using the proposed method, the EER of iris recognition was reduced as much as 0.133% (1.485% - 1.352%) in comparison with that by using bi-linear interpolation

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1101-1104
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• 1995

Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1361-1369
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• 1999

A hit-miss transform(HMT) using modified synthetic structuring elements(SEs) for distortion-invariant recognition of multiple objects is proposed. A fundamental problem in an HMT is the determination of the optimal SE needed to improve the false alarm rate, and detect distorted objects with various shapes. The proposed synthetic methods of SE provide good solutions against this problem. One is the multistage synthesis of each true class SE using only set theory, and the other is the multistage synthesis of each true class and false class SE using set theory and SDF(synthetic discriminant function) synthesis method. Simulation results show the proposed methods can be used for the recognition of distorted intraclass objects and the discrimination of similar interclass objects.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.213-213
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• 2016

현재 반도체 산업에서는 디바이스의 고 집적화, 고 수율을 목적으로 패턴의 미세화 및 웨이퍼의 대면적화와 같은 이슈가 크게 부각되고 있다. 다중 패터닝(multiple patterning) 기술을 통하여 고 집적 패턴을 구현이 가능해졌으며, 이와 같은 상황에서 각 패턴의 임계치수(critical dimension) 변화는 패턴의 위치 및 품질에 큰 영향을 끼치기 때문에 포토마스크의 임계치수 균일도(critical dimension uniformity, CDU)가 제작 공정에서 주요 파라미터로 인식되고 있다. 반도체 광 리소그래피 공정에서 크롬(Cr) 박막은 사용되는 포토 마스크의 재료로 널리 사용되고 있으며, 이러한 포토마스크는 fused silica, chrome, PR의 박막 층으로 이루어져 있다. 포토마스크의 패턴은 플라즈마 식각 장비를 이용하여 형성하게 되므로, 식각 공정의 플라즈마 균일도를 계측하고 관리 하는 것은 공정 결과물 관리에 필수적이며 전체 반도체 공정 수율에도 큰 영향을 미친다. 흔히, 포토마스크 임계치수는 플라즈마 공정에서의 라디칼 농도 및 식각 선택비에 의해 크게 영향을 받는 것으로 알려져 왔다. 본 연구에서는 Cr 포토마스크 에칭 공정에서의 Cl2/O2 공정 플라즈마에 대해 O2 가스 주입량에 따른 식각 선택비(etch selectivity) 변화를 계측하여 선택비 제어를 통한 Cr 포토마스크 임계치수 균일도 향상을 실험적으로 입증하였다. 연구에서 사용한 플라즈마 계측 방법인 발광분광법(OES)과 optical actinometry의 적합성을 확인하기 위해서 Cl2 가스 주입량에 따른 actinometer 기체(Ar)에 대한 atomic Cl 농도비를 계측하였고, actinometry 이론에 근거하여 linear regression error 1.9%을 보였다. 다음으로, O2 가스 주입비에 따른 Cr 및 PR의 식각률(etch rate)을 계측함으로써 식각 선택비(etch selectivity)의 변화율이 적은 O2 가스 농도 범위(8-14%)를 확인하였고, 이 구간에서 임계치수 균일도가 가장 좋을 것으로 예상할 수 있었다. (그림 1) 또한, spatially resolvable optical emission spectrometer(SROES)를 사용하여 플라즈마 챔버 내부의 O atom 및 Cl radical의 공간 농도 분포를 확인하였다. 포토마스크의 임계치수 균일도(CDU)는 챔버 내부의 식각 선택비의 변화율에 강하게 영향을 받을 것으로 예상하였고, 이를 입증하기 위해 각각 다른 O2 농도 환경에서 포토마스크 임계치수 값을 확인하였다. (표1) O2 11%에서 측정된 임계치수 균일도는 1.3nm, 그 외의 O2 가스 주입량에 대해서는 임계치수 균일도 ~1.7nm의 범위를 보이며, 이는 25% 임계치수 균일도 향상을 의미함을 보인다.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.33-40
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• 2000

In this study, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements that are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have the characteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.67-75
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• 1999

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D image into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that primitive elements are extracted too much to represent and to describe the shape. To solve these problems, a new shape decomposition algorithm using primitive elements tat are similar to the geometrical characteristics of shape and 4 scan modes is proposed in this study. The multiple primitive elements as circle, square, and rhombus are extracted by using multiscan modes in a new algorithm. This algorithm have chatacteristics that description error and number of primitive elements is reduced. Then, description efficiency is improved. The procedures is also simple and the processing time is reduced.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.77-85
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• 2011

It is believed that the anomalies or diseases of human organs are identified by the analysis of the patterns. This paper proposes a new classification technique for the identification of cancer disease using the proteome patterns obtained from two-dimensional polyacrylamide gel electrophoresis(2-D PAGE). In the new classification method, three different classification methods such as support vector machine(SVM), multi-layer perceptron(MLP) and k-nearest neighbor(k-NN) are extended by multi-boosting method in an array of subclassifiers and the results of each subclassifier are merged by ensemble method. Genetic algorithm was applied to obtain optimal feature set in each subclassifier. We applied our method to empirical data set from cancer research and the method showed the better accuracy and more stable performance than single classifier.