• Title/Summary/Keyword: discontinuity detection

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Discontinuity Detection in the DCT Domain for Real-Time Processing (실시간 처리를 위한 DCT 영역에서의 불연속 경계 검출)

  • Kim, Tae-Yong;Han, Jun-Hui
    • Journal of KIISE:Software and Applications
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    • v.28 no.2
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    • pp.141-148
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    • 2001
  • DCT(Discrete Cosine Transform) 변환은 MPEG과 JPEG 표준에 의하여 영상이나 비디오 영상을 압축하는데 사용되어져 왔다. 본 연구에서는 이상적인 경계가 관련된 특성을 유도하고, 실시간 처리를 위하여 모델에 바탕을 둔 DCT 영역에서의 불연속 경계 평가 방법을 제안한다. 이 방법은 방향 검증과 위치 정렬 등의 평가로 구성된다. 두 가지의 평가 방법에 의하여 경계의 다양한 방향과위치를 알 수 있으며, DCT 계수들을 표준화된 형식으로 정렬시킬 수 있고, 표준화된 DCT 계수에서 이상적인 계단 경계의 특성과 비교하여 경계의 크기를 산출할 수 있다. DCT 계수가 8x8의 블록 단위로 이루어져 있어 경계의 표현이 조밀하지는 않지만 처리 시간이 빠르고 잡음에 강한 특성을 가지고 있어 다양한 실시간 응용분야에 사용될 수 있을 것이다.

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Detection of Abnormal Region of Skin using Gabor Filter and Density-based Spatial Clustering of Applications with Noise (가버 필터와 밀도 기반 공간 클러스터링을 이용한 피부의 이상 영역 검출)

  • Jeon, Minseong;Cheoi, Kyungjoo
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.117-129
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    • 2018
  • In this paper, we suggest a new system that detects abnormal region of skim. First, an illumination elimination algorithm which uses LAB color model is processed on input facial image to obtain robust facial image for illumination, and then gabor filter is processed to detect the reactivity of discontinuity. And last, the density-based spatial clustering of applications with noise(DBSCAN) algorithm is processed to classify areas of wrinkles, dots, and other skin diseases. This method allows the user to check the skin condition of the images taken in real life.

Estimation of Jump Points in Nonparametric Regression

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.899-908
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    • 2008
  • If the regression function has jump points, nonparametric estimation method based on local smoothing is not statistically consistent. Therefore, when we estimate regression function, it is quite important to know whether it is reasonable to assume that regression function is continuous. If the regression function appears to have jump points, then we should estimate first the location of jump points. In this paper, we propose a procedure which can do both the testing hypothesis of discontinuity of regression function and the estimation of the number and the location of jump points simultaneously. The performance of the proposed method is evaluated through a simulation study. We also apply the procedure to real data sets as examples.

Evaluation Technology for the Flaw Sizing of Generator Rotor by Using Phased Array Ultrasonic Technique (위상배열 초음파기법을 이용한 발전기 로터 결점크기 평가)

  • Kim, Jin-Hoi;Park, Cher-Young;Lee, Sang-Hoon
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.5 no.1
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    • pp.14-19
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    • 2009
  • NDE(Nondestructive examination) detects a flaw or discontinuity in materials. Flaws detected by the examination shall be evaluated for the decision basis of the integrity. The internal flaws of forging products can be detected by UT. However, UT has detection limits because of its reflected signal weakness. Normally, a 1mm or less flaw is known as the limit. If a flaw was detected, the size of flaw would be evaluated by AVG(or DGS) technique. To verify the evaluation data, alternative examination methods are needed. But there is no alternative examination methods until now. In this study, Phased array ultrasonic technique can be used to size the flaws in the generator rotor with focused beam of ultrasonic wave as a supplement method of AVG. Also, the phased array ultrasonic technique described enables the shape of flaw to be depicted exactly.

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A Research on Developing the Fault Tolerant Control System using Restructurable Control Method (구조 변경 제어 방식을 이용한 고장 허용 제어 시스템 설계에 관한 연구)

  • Hong, Ho-Taek;Kim, Yong-Min;Park, Jae-Hong
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1259-1263
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    • 1999
  • In this paper, a method to guarantee system continuity is developed, which can be applied to discontinuity problem in the time domain of restructurable control system. This method can be summarized as input alternation using weight change considering convergence speed of system mode. Input is changed from 'system continuity guarantee input,' which is defined as a input that minimizes the change of state variables, to 'alternative controller input,' which is selected by Neil's PI/EAM[3]. AIDC aircraft model is used for simulation. By showing the waveform of system input and state variable, we can sure that this method is effective for depression of system shock like jerk.

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Stochastic Model for Unification of Stereo Vision and Image Restoration (스테레오 비젼 및 영상복원 과정의 통합을 위한 확률 모형)

  • Woo, Woon-Tak;Jeong, Hong
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.9
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    • pp.37-49
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    • 1992
  • The standard definition of computational vision is a set of inverse problems of recovering surfaces from images. Thus the common characteristics of the most early vision problems are ill-posed. The main idea for solving ill-posed problems is to restrict the class of admissible solutions by introducing suitable a priori knowledge. Standard regurarization methods lead to satisfactory solutions of early vision problems but cannot deal effectively and directly with a few general problems, such as discontinuity and fusion of information from multiple modules. In this paper, we discuss limitations of standard regularization theory and present new stochastic method. We will outline a rigorous approach to overcome part of ill-posedness of image restoration, edge detection, and stereo vision problems, based on Bayes estimation and MRF(Markov random field) model, that effectively deals with the problems. This result makes one hope that this framework could be useful in the solution of other vision problems.

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A New Interpretation of the Compass Gradient Edge Operators (Compass Gradient Edge 연산자의 새로운 해석방법)

  • Park, Rae-Hong;Choi, Woo Young
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.24 no.1
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    • pp.97-101
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    • 1987
  • The edge, a discontinuity or abrupt change in the gray-level or color, is a fundamentally important primitive feature of an image necessary for the image analysis and classification. Two-dimensional 3x3 compass gradient operators (ex. Sobel, Prewitt, and Kirsch operators)are commonly used in the edge detection and usually detect 8 compass directional components. In this paper, we present a new interpretation of the relationships between the resulting 8 gradient magnitudes and the 8 intensity values of neighboring pixels which are covered by the two-dimensional 3x3 mask. It is expected that a new gradient edge operator may be designed by changing the eigenvalues in the transform domain and the fast optical edge operator may be implemented by using the optical system.

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Study on the Qualitative Defects Detection in Composites by Optical Infrared Thermography (적외선 열화상 기술을 이용한 복합재료의 결함 검출 정량화 연구)

  • Park, Hee-Sang;Choi, Man-Yong;Park, Jeong-Hak;Kim, Won-Tae;Choi, Won-Jong
    • Journal of the Korean Society for Nondestructive Testing
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    • v.31 no.2
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    • pp.150-156
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    • 2011
  • In this paper, infrared thermography measurement technique has been used to develop standard measurement technique for nondestructive testing of composite materials which is widely used in aerospace industries. To increase the defect detection rate, the related experiment used the lock-in IR-thermographiy method. Therefore it is of considerable interest in the field of non-destructive testing for fast discontinuity detection by using ultrasonic lock-in infrared thermography. The result also shows that as the investigation period of light source is lengthened according to the thickness of specimen, the possibility of detecting defects gets higher as well. However, the reason why the result values were not favorable when less than 50 mHz of light source was provided is because it was difficult to detect defects as the defect parts became a state of thermal equilibrium in general when thermal diffusivity affects the entire materials.

Technique of Seam-Line Extraction for Automatic Image Mosaic Generation (자동 모자이크 영상제작을 위한 접합선 추출기법에 관한 연구)

  • Song, Nak-Hyeon;Lee, Sung-Hun;Oh, Kum-Hui;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.1
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    • pp.47-53
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    • 2007
  • Satellite image mosaicking is essential for image interpretation and analysis especially for a large area such as the Korean Peninsula. This paper proposed the technique of automatic seam-line extraction and the method of creating image mosaic in automated fashion. The seam-line to minimize artificial discontinuity was extracted using Minimum Absolute Gray Difference Sum algorithm with constraint condition on search-area width and Canny Edge Detection algorithm. To maintain the radiometric balance among images acquired at different time epochs, we utilized Match Cumulative Frequency method. Experimental results showed that edge detection algorithm extracted the seam-lines significantly well along linear features such as roads and rivers.

Research Trend Analysis for Fault Detection Methods Using Machine Learning (머신러닝을 사용한 단층 탐지 기술 연구 동향 분석)

  • Bae, Wooram;Ha, Wansoo
    • Economic and Environmental Geology
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    • v.53 no.4
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    • pp.479-489
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    • 2020
  • A fault is a geological structure that can be a migration path or a cap rock of hydrocarbon such as oil and gas, formed from source rock. The fault is one of the main targets of seismic exploration to find reservoirs in which hydrocarbon have accumulated. However, conventional fault detection methods using lateral discontinuity in seismic data such as semblance, coherence, variance, gradient magnitude and fault likelihood, have problem that professional interpreters have to invest lots of time and computational costs. Therefore, many researchers are conducting various studies to save computational costs and time for fault interpretation, and machine learning technologies attracted attention recently. Among various machine learning technologies, many researchers are conducting fault interpretation studies using the support vector machine, multi-layer perceptron, deep neural networks and convolutional neural networks algorithms. Especially, researchers use not only their own convolution networks but also proven networks in image processing to predict fault locations and fault information such as strike and dip. In this paper, by investigating and analyzing these studies, we found that the convolutional neural networks based on the U-Net from image processing is the most effective one for fault detection and interpretation. Further studies can expect better results from fault detection and interpretation using the convolutional neural networks along with transfer learning and data augmentation.