• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.7
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• pp.807-818
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• 1988

This paper proposes new algorithms for the estimation of displacement vector and moving object extraction using difference picture. First, the relations between the boundary of moving objects in two consecutive image and the boundary of difference picture regions are analyzed, then displacement vector estimation algorithm is proposed. Using the estimated displacement vector, moving objects are directly extracted from difference picture. Since the proposed algorithms do not process gray-valued image, they have a short processing time and are suitable to real time processing. From the experimental results, we observed that, if difference picture is wel extracted, the proposecd algorithms work well even in the circumstances of complex background, fast or slow motion, rotation etc., including occlusion where is not moving area.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.182-185
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• 1986

In this paper, the four algorithm which obtain 2D displacement vector are proposed. In corwocutive difference pictures, the characteristics of up DP boundary and region are discussed and we estimate displacement vector using the DP boundary and region, Finally, the performance of proposed algorithm for gaussian noisy image which generated by computer are discussed.

• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.251-257
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• 2017

A local damage identification method using measured structural static displacement is proposed in this study. Based on the residual force vector deduced from the static equilibrium equation, residual strain energy (RSE) is introduced, which can localize the damage in the element level. In the case of all the nodal displacements are used, the RSE can localize the true location of damage, while incomplete displacement measurements are used, some suspicious damaged elements can be found. A model updating method based on static displacement response sensitivity analysis is further utilized for accurate identification of damage location and extent. The proposed method is verified by two numerical examples. The results indicate that the proposed method is efficient for damage identification. The advantage of the proposed method is that only limited static displacement measurements are needed in the identification, thus it is easy for engineering application.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.349-354
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• 2010

Moving pixel displacement detection algorithm using correlation functions for making panorama image on the continuous images is presented in this paper. The input images get from a CMOS image sensor (CIS). The camera is maintained by constant brightness and uniform sensing area in test input pattern. For simple navigation and capture image has to 70% overlapped region. A correlation rate in two image data is evaluated by using reference image with first captures, and compare image with next captures. The displacement of the two images are expressed to second order function of x, y and solved with finding the coefficient in second order function. That results in the change in the peak correlation displacement from the reference to the compare image, is moving to pixel length. The navigating error is reduced by varying the path because the error is shown in the difference of the positioning vector between the true pixel position and the navigated pixel position. The algorithm performance is evaluated to be different from the error vector to vary the navigating path grid.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.322-332
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• 2007

We consider a deformation method suitable for fractal. In IFS fractal, the position of a point is characterized by its code as well as by its coordinates. Code has a meaning of address for fractal. If we move a point by changing its code, the resulting movement shows fractal behavior. We propose three deformation methods based on code information. For the deformation vector of a point in fractal, 1) we use the vector of a given vector field at the point obtained by code transformation, 2) we use the vector constructed by adding predefined displacement vectors according to the code information of the point. Both methods show a fractal-like character as well as an ordinary continuous deformation character. Also, 3) we can deform fern-fractal more naturally by restricting its deforming region using code form.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.156-159
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• 2003

Surface normal vector and surface velocity are very important parameters to simulate rolling processes precisely. In this study, Local displacement functions are constructed for each node on the contact surface and parameters are found by the least square fitting of displacement on the neighbor nodes. Deformation gradient tensor is calculated from the displacement function and surface normal vector and velocity also can be derived. Flat rolling simulation model is presented on the basis of the suggested contact scheme. Series of rolling process simulation are carried out and the results are compared with the experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1477-1485
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• 2003

The displacement vector field can be represented in terms of a scalar potential ${\phi}$ and a vector potential ${\phi}$. The scalar potential ${\phi}$ is related to dilatational waves and the vector potential ${\phi}$ is related to rotational waves. Using these two complex displacement potentials, the stress and displacement fields for steadily growing interface cracks in dissimilar materials are obtained. The energy release rate for steadily growing interface cracks in dissimilar materials are also obtained. And with photoelastic isochromatic patterns simulated by computer graphics, the stress intensity factors are discussed.

• Journal of Korean Society of Steel Construction
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• v.9 no.4 s.33
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• pp.467-477
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• 1997

A series of experimental tests have been performed on a tube beam in which artificial damage is applied in order to address damage detectability using modal analysis. Modal parameters considered are frequency, displacement mode shape and strain mode shape CoMAC(Coordinate Modal Assurance Criterion) and Modal Vector Error have been adopted for presenting the change of displacement mode shape and strain mode shape. It is revealed strain mode shape is the most sensitive to damage.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.937-945
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• 2014

Multi-modal biometric system can use another biometric trait in the case of having deficiency at a biometric trait. It also has an advantage of improving the performance of personal identification by using multiple biometric traits, so studies on new biometric traits have continuously been performed. The inner face of finger is a relatively new biometric trait. It has two major features of knuckle lines and wrinkles, which can be used as discriminative features. This paper proposes a finger identification method based on displacement vector to effectively process some variation appeared in contactless hand image. At first, the proposed method produces displacement vectors, which are made by connecting corresponding points acquired by matching each pair of local block. It then recognize finger by measuring the similarity among all the detected displacement vectors. The experimental results using pubic CASIA hand image database show that the proposed method may be effectively applied to personal identification.