• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.6
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• pp.736-743
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• 2003

A process of 3-D particle image velocimetry, called here, as '3-D stereo PIV' was developed for the measurement of an illuminated slied section field of 3-D complex flows. The present method includes modeling of camera by a calibrator based on the homogeneous coordinate system, transfromation of the oblique-angled image to the right-angled image, identification of 2-D velocity vectors by 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criterior, and finally 3-D animation as the post processing. An experimental system was also used for the application of the proposed method. Three analog CCD cameras and an Argon-Ion Laser(300mW) for illumination were adopted to capture the wake flow behind a bluff obstacle.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.658-663
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• 2003

A process of 3-D stereo particle image velocimetry(PIV)was developed for the measurement of an illuminated sliced section field of 3-D complex flows. The present method includes modeling of camera by a calibrator based on the homogeneous coordinate system, transformation of the oblique-angled image to the right-angled image, identification of 2-D velocity vectors by 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criteria, and finally 3-D display as the post processing. An experimental system was also used for the application of the proposed method. Two high speed digital CCD cameras and an Argon-Ion Laser for the illumination were adopted to clarify the time-dependent characteristics of the leading edge extension(LEX) in a highly swept shape applied to a delta wing found in modern air-fighters.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.94-95
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• 2016

스테레오 정합은 서로 다른 두 시점을 갖는 스테레오 영상으로부터 객체의 깊이값을 예측한다. 이 방법은 객체가 카메라로 부터 멀리 떨어질수록 두 시점 사이에 큰 변위차를 갖는 양안시차 특성을 이용해 깊이값을 구한다. 일반적으로 스테레오 정합은 촬영한 두 영상의 조명 변화 및 노출 정도가 같다는 조건으로 수행된다. 하지만 실내 또는 실외에서 실제로 영상을 촬영하면 조명 및 햇빛의 위치 그리고 카메라의 특성에 따라 촬영된 스테레오 영상의 밝기가 서로 달라지는 경우가 발생하게 된다. 이처럼 두 영상의 밝기차를 고려하지 않고 스테레오 정합을 하게 되면 정확한 깊이값을 예측하기 어렵다. 이러한 문제를 개선하기 위해 조명 변화에 강인한 ANCC (Adaptive Normalized Cross Correlation)가 제안되었다. 이 방법은 영상 속 화소들의 색상 모델을 이용해 조명변화의 영향을 받는 요소들을 제거함으로써 다양한 밝기변화 속에서도 안정적으로 스테레오 정합을 수행할 수 있도록 한다. 하지만 ANCC는 수행과정에서 각 화소마다 양방향 필터 (Bilateral Filter)가 적용되는 등 높은 복잡도를 갖는다는 단점이 있다. 본 논문에서는 기존의 ANCC 보다 복잡도가 낮으면서 밝기변화에도 안정적인 정합 결과를 갖기 위해 Census 변환의 이진 정보를 이용한 스테레오 정합 방법을 제안한다.

• 한국가시화정보학회:학술대회논문집
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• 2002.11a
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• pp.19-22
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• 2002

A process of 3-D particle image velocimetry, called here, as '3-D stereo PIV' was developed for the measurement of a section field of 3-D complex flows. The present method includes modeling of camera by a calibrator based on the homogeneous coordinate system, transfromation of oblique-angled image to transformed image, identification of 2-D velocity vectors by 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system and finally 3-D animation as the post processing. In principle, as two frame images only are necessary for the single instantaneous analysis of a section field of 3-D flow, more effective vectors are obtainable contrary to the previous multi-frame vector algorithm. An experimental system was also used for the application of the proposed method. Three analog CCD cameras and an Argon-Ion Laser(300mW) for illumination were adopted to capture the wake flow behind a bluff obstacle.

• Korean Journal of Remote Sensing
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• v.9 no.2
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• pp.7-19
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• 1993

In stereo vision, when we use two parallel axis images, small portion of object is contained and B/H(Base-line to Height) ratio is limited due to the size of object and depth information is inaccurate. To overcome these difficulities we take a non-parallel axis image which is rotated $\theta$ about y-axis and match other parallel-axis image. Epipolar lines of non-parallel axis image are not same as those of parallel-axis image and we can't match these two images directly. In this paper, we transform the non-parallel axis image geometrically with camera parameters, whose epipolar lines are alingned parallel. NCC(Normalized Cross Correlation) is used as match measure, area-based matching technique is used find correspondence and 9$\times$9 window size is used, which is chosen experimentally. Focal length which is necessary to get depth information of given object is calculated with least-squares method by CCD camera characteristics and lenz property. Finally, we select 30 test points from given object whose elevation is varied to 150 mm, calculate heights and know that height RMS error is 7.9 mm.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.375-382
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• 2016

In this paper, we presents a signatures verification by using the nonlinear quantization histogram of polar coordinate based on multi-dimensional adjacent pixel intensity difference. The multi-dimensional adjacent pixel intensity difference is calculated from an intensity difference between a pair of pixels in a horizontal, vertical, diagonal, and opposite diagonal directions centering around the reference pixel. The polar coordinate is converted from the rectangular coordinate by making a pair of horizontal and vertical difference, and diagonal and opposite diagonal difference, respectively. The nonlinear quantization histogram is also calculated from nonuniformly quantizing the polar coordinate value by using the Lloyd algorithm, which is the recursive method. The polar coordinate histogram of 4-directional intensity difference is applied not only for more considering the corelation between pixels but also for reducing the calculation load by decreasing the number of histogram. The nonlinear quantization is also applied not only to still more reflect an attribute of intensity variations between pixels but also to obtain the low level histogram. The proposed method has been applied to verified 90(3 persons * 30 signatures/person) images of 256*256 pixels based on a matching measures of city-block, Euclidean, ordinal value, and normalized cross-correlation coefficient. The experimental results show that the proposed method has a superior to the linear quantization histogram, and Euclidean distance is also the optimal matching measure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

• 한국가시화정보학회:학술대회논문집
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• 2003.11a
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• pp.39-42
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• 2003

Leading edge extension(LEX) in a highly swept shape applied to a delta wing features the modern air-fighters. The LEX vortices generated upon the upper surface of the wing at high angle of attack enhance the lift force of the delta wing by way of increased negative suction pressure over the surfaces. The present 3-D stereo PIV includes the Identification of 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criterion and so on. A delta wing model with or without LEX was immersed in a circulating water channel. Two high-resolution, high-speed digital cameras$(1280pixel\times1024pixel)$ were used to allow the time-resolved animation work. The present dynamic stereo PIV represents the complicated vortex behavior, especially, in terms of time-dependent characteristics of the vortices at given measuring sections. Quantities such as three velocity vector components, vorticity and other flow information can be easily visualized via the 3D time-resolved post-processing to make the easy understanding of the LEX effect or vortex emerging and collapse which are important phenomena occurring in the field of delta wing aerodynamics.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.301-304
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• 2008

Since longer wavelength microwave radiation can penetrate clouds, satellite passive microwave sensors can observe sea ice of the entire polar region on a daily basis. Thus, it is becoming popular to derive sea ice motion vectors from a pair of satellite passive microwave sensor images observed at one or few day interval. Usually, the accuracies of derived vectors are validated by comparing with the position data of drifting buoys. However, the number of buoys for validation is always quite limited compared to a large number of vectors derived from satellite images. In this study, the sea ice motion vectors automatically derived from pairs of AMSR-E 89GHz images (IFOV = 3.5 ${\times}$ 5.9km) by an image-to-image cross correlation were validated by comparing with sea ice motion vectors manually derived from pairs of cloudless MODIS images (IFOV=250 ${\times}$ 250m). Since AMSR-E and MODIS are both on the same Aqua satellite of NASA, the observation time of both sensors are the same. The relative errors of AMSR-E vectors against MODIS vectors were calculated. The accuracy validation has been conducted for 5 scenes. If we accept relative error of less than 30% as correct vectors, 75% to 92% of AMSR-E vectors derived from one scene were correct. On the other hand, the percentage of correct sea ice vectors derived from a pair of SSM/I 85GHz images (IFOV = 15 ${\times}$ 13km) observed nearly simultaneously with one of the AMSR-E images was 46%. The difference of the accuracy between AMSR-E and SSM/I is reflecting the difference of IFOV. The accuracies of H and V polarization were different from scene to scene, which may reflect the difference of sea ice distributions and their snow cover of each scene.