• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.997-1003
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• 2007

In this paper, we propose a global approach for automatic inspection of defects in the polarizer film image. The proposed method does not rely on local feature of the defect. It is based on a global image reconstruction scheme using the singular value decomposition(SVD). SVD is used to decompose the image and then obtain a diagonal matrix of the singular values. Among the singular values, the first singular value is used to reconstruct a image. In reconstructed image, the normal pixels in background region have a different characteristics from the pixels in defect region. It is obtained the ratio of pixels in the reconstructed image to ones in the original image and then the defects are detected based on the the statistical process of the ratio. The experiment results show that the proposed method is efficient for defect inspection of polarizer lam image.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.755-760
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• 2009

In this paper, we apply a reverberation suppression method using difference of singular values to improve the short-distance underwater obstacle detection probability in reverberation environment induced by a linear frequency modulation signal. The reverberation suppression method using difference of singular values suppresses LFM reverberation based on subtracting the singular values for a reference beam, assumed to contain only the reverberation, from those for the current beam of interest, assumed to contain the reverberation and target echo. For the validation, the reverberation suppression method using difference of singular values is applied to real oceanic data, which are acquired using the cross type array.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.165-169
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• 2009

오늘날 인터넷 검색은 하루가 다르게 발전되고 있다. 주로 키워드 매칭에 의존을 둔 지금의 검색 서비스들은 사용자 중심의 아이템들을 개발해 정보검색의 경과시간 및 결과의 분류면에서 우수함을 보여주고 있다. 질의어의 의미에 유사한 검색은 아직은 발전하는 단계로, 내용에 기반을 둔 검색 환경에 초점이 맞춰지고 있다. 이와 관련하여 행렬의 특이치 분해(SVD)를 이용한 잠재적 의미 색인 기법(LSI)을 본 연구에서 다루고자 한다. 구축한 시스템의 성능 평가는 재현도 계산으로 비교되었는데 작은 크기의 특이값(singular value)들 생략에 의한 SVD의 성능과 그것을 재이용, 질의어에 대한 의미 구조상 근접한 용어들을 찾아 질의어를 확장한 후 적합한 문서들의 검색을 사용한 특이값 개수, 유사단어 확장 개수를 달리하여 실험하였다. 실험 결과, 특이값 2개를 사용한 잠재적 의미 색인이 특이값 3개를 사용한 잠재적 의미 색인보다 보다 나은 성능을 보였다. 그리고 조건을 달리한 모든 잠재적 의미 색인의 경우 단어 매칭에 의한 적합문서 검색보다 별 뚜렷한 나은 결과는 보이지 않았다. 하지만 의미적으로 관계가 깊은 유사어들을 찾아냈고, 의미적으로 가장 관계 깊은 문서를 대부분의 경우에서 순위 1위로 찾아내는 부분적 우수함을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.28-30
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• 2011

본 논문에서는 특이값 분해(Singular Value Decomposition)을 이용하여 이미지의 주파수 영역 내에 정보를 은닉하는 방법을 제시한다. 이미지를 주파수 영역으로 변환하기 위하여 블록 단위로 이산 코사인 변환(Discrete Cosine Transform)을 수행한다. 이후 인접한 네 블록의 DC 값들로 구성된 행렬의 특이값을 은닉하고자 하는 정보에 따라 변환한다. 원래의 DC 값은 정보에 따라 변환된 DC 값으로 대체되고 역 이산 코사인 변환(Inverse Discrete Cosine Transform)을 수행하여 정보가 은닉된 이미지를 얻는다. 제안하는 알고리즘의 성능을 분석하기 위해 JPEG(Joint Photographic Coding Experts Group), 선명화(Sharpening), 히스토그램 등화(Histogram Equalization)와 같이 다양한 이미지 변화를 거친 후, 은닉된 정보의 신뢰도를 비교한다.

• The Journal of the Acoustical Society of Korea
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• v.12 no.2
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• pp.28-36
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• 1993

임의의 형상을 갖는 진동체에 의한 방사 음장해석은 경계요소법에 의하여 이미 많은 해석이 시도되었다. 그러나, 진동체의 형상이 매우 복잡한 경우에는 겉표면의 요소수가 크게 증가할 뿐만 아니라 각 요소에서의 경계조건을 모두 알아내어야 하므로, 저주파에 국한된 해석일지라도 엄청난 시간과 노력이 필요하게 된다. 이러한 어려움을 극복하기 위하여 경계요소법을 사용하되, 복잡한 형상의 진동체를 둘러싸는 가상적인 표면을 매우 간단하게 설정한 후 그 표면상의 경계조건인 음압을 측정한다. 임의의 형상에 대한 파수 영역에서의 감쇠파의여파작업을 위하여 특이값 분리를 사용하였다. 특이값 분리에 의하여 음압분포를 측정위치에서 설정된 일반 좌표계에서의 고유모드로 분해한다. 각 고유모드의 원거리 음장의 기여도에 해당하는 각 특이벡터에 대한 특이값의 크기를 비교하여, 유한개의 고유모드만을 포함시킴으로써 원거리 음장을 예측한다. 몇 개의 예제를 통하여 해석적 방법의 기존의 경계요소법에 의한 결과를 본 연구 방법의 결과와 비교하여 잘 일치함을 확인하였다.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.465-473
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• 2018

The application of singular value decomposition (SVD) filtering is examined for attenuation of the ground-roll in land seismic data. Prior to the SVD computation to seek singular values containing the highly correlatable reflection energy, processing steps such as automatic gain control, elevation and refraction statics, NMO correction, and residual statics are performed to enhance the horizontal correlationships and continuities of reflections. Optimal parameters of SVD filtering are effectively chosen with diagnostic display of inverse NMO (INMO) corrected CSP (common shot point) gather. On the field data with dispersion of ground-roll overwhelmed, continuities of reflection events are much improved by SVD filtering than f-k filtering by eliminating the ground-roll with preserving the low-frequency reflections. This is well explained in the average amplitude spectra of the f-k and SVD filtered data. The reflectors including horizontal layer of the reservoir are much clearer on the stack section, with laminated events by SVD filtering and subsequent processing steps of spiking deconvolution and time-variant spectral whitening.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.395-407
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• 2007

Outliers distort many measures for data analysis. We can propose dandelion seed plot as a graphical tool for evaluating the effect of outliers in one-and two-variate data. We can draw mean-variance dandelion seed plots using linked curves which are made by changing weights from 1 to 0 for each datum. Similarly we can also draw covariance-correlation-coefficient dandelion seed plots. This graphical method can be a useful tool for elementary statistics education in college.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.481-489
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• 2011

In this paper presents new force method by using singular value decomposition. The existing force method has some advantages about analysis of truss structures such as it is easier basic concept than finite element method, which apply to analyze truss structures. However, this method has complex formulation for analysis. Therefore, in this study proposes new force method using singular value decomposition, which is both having easy basic concept and simple computation than existing force method. The proposed method is illustrated through numerical examples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.89-96
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• 2013

This paper presents an improved clutter signal removal algorithm using Singular Value Decomposition(SVD). For indoor positioning system using IR-UWB Radar, the target signal is extracted from received signal. We use clutter signal removal algorithm using SVD for target signal extraction. Clutter signal removal algorithm using SVD has the advantage of operation but the disadvantage of high computational complexity. In this paper, we propose a method to improve computational complexity. As the experimental results, it is confirmed that the method presented in this paper improve the computational complexity of clutter removal algorithm using SVD.