• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.1-11
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• 2010

This study aims to improve the more confident and efficient projection method that is to estimate the Number of Household per Family scales(NHF) in projecting the Household Heath care Expenditure(HHE). For this purpose, this paper suggested three results of the research. First, because projecting the NHF does not reflect the recent socio-demographic trends in the process of projecting the National Health Expenditure(NHE),the prior projection results have serious problem in the confidence and political availability. Second, the projection results about the HHE might be underestimated relative to the real one. Third, in order to estimate the more confident and efficient estimates of the HHE, the estimated NHF reflecting the socio-demographic trend must be used to project the one. There is an alternative method that the NHF and the increasing or decreasing rate of them which are regularly surveyed and suggested by the KOSIS should be used to project the process.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.209-214
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• 2010

This paper proposes an algorithm of segmentation and title detection for document image. The automated title detection method that we have developed is composed of two phases, segmentation and title area detection. In the first phase, we extract and segment the document image. To perform this operation, the binary map is segmented by combination of morphological operation and CCA(connected component algorithm). The first phase provides segmented regions that would be detected as title area for the second stage. Candidate title areas are detected using geometric information, then we can extract the title region that is performed by removing non-title regions. After classification step that removes non-text regions, projection is performed to detect a title region. From the fact that usually the largest font is used for the title in the document, horizontal projection is performed within text areas. In this paper, we proposed a method of segmentation and title detection for various forms of document images using geometric features and projection profile analysis. The proposed system is expected to have various applications, such as document title recognition, multimedia data searching, real-time image processing and so on.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3194-3216
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• 2018

Slow Feature Discriminant Analysis (SFDA) is a supervised feature extraction method inspired by biological mechanism. In this paper, a novel method called Two Dimensional Slow Feature Discriminant Analysis via $L_{2,1}$ norm minimization ($2DSFDA-L_{2,1}$) is proposed. $2DSFDA-L_{2,1}$ integrates $L_{2,1}$ norm regularization and 2D statically uncorrelated constraint to extract discriminant feature. First, $L_{2,1}$ norm regularization can promote the projection matrix row-sparsity, which makes the feature selection and subspace learning simultaneously. Second, uncorrelated features of minimum redundancy are effective for classification. We define 2D statistically uncorrelated model that each row (or column) are independent. Third, we provide a feasible solution by transforming the proposed $L_{2,1}$ nonlinear model into a linear regression type. Additionally, $2DSFDA-L_{2,1}$ is extended to a bilateral projection version called $BSFDA-L_{2,1}$. The advantage of $BSFDA-L_{2,1}$ is that an image can be represented with much less coefficients. Experimental results on three face databases demonstrate that the proposed $2DSFDA-L_{2,1}/BSFDA-L_{2,1}$ can obtain competitive performance.

• Speech Sciences
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• v.13 no.1
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• pp.117-128
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• 2006

The two-channel Generalized Sidelobe Canceller (GSC) scheme suffers from the presence of leakage signal in the reference channel. The leakage signal is caused by the dissimilar impulse responses between microphones, and different paths from speech source to microphones. Such leakage is detrimental to speech enhancement of the GSC since the desired reference signal becomes corrupted. In order to suppress the signal leakage, two matrix injection methods are proposed. In the first method, a simple gain compensation matrix is used. In the second, a projection matrix for reducing the error between the actual and the ideal primary and reference signals, is used. This paper describes the performance degradation resulting from leakage, and proposes effective methods to resolve the problem. Representative experiments were conducted to demonstrate the effectiveness of the proposed methods on recorded speech and noise in an actual automobile environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.17-24
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• 2018

Polar fomat algorithm (PFA) was derived from medical imaging theory, known as back projection, to process synthetic aperture radar(SAR) data. The difference between the operating condition of SAR and back projection assumption makes two distortions. First, the focusing performance of PFA is degraded in proportion to distances from the scene center. Second, the geometric accuracy in SAR images is distorted. Several methods were introduced to mitigate the distortions, but some disadvantages, such as the geometric discontinuity, are arisen when sub-images are combined. This paper proposes the novel method to compensate the geometric distortion with chirp Z-transform (CZT). This method corrects precisely the geometric errors without any problems, because a whole image can be processed all at once.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.77-82
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• 2013

The object tracking method using particle filtering has been proved successful since it is based on the Monte Carlo simulation to estimate the posterior distribution of the state vector that is nonlinear and non-Gaussian in the real-world situation. In this paper, we present two nobel methods that can improve the performance of the object tracking algorithm based on the particle filtering. First one is the feedback method that replace the low-weighted tracking sample by the estimated state vector in the previous frame. The second one is an tracking box correction method to find an confidence interval of back projection probability on the estimated candidate object area. An sample propagation equation is also presented, which is obtained by experiments. We designed well-organized test data set which reflects various challenging circumstances, and, by using it, experimental results proved that the proposed methods improves the traditional particle filter based object tracking method.

• Journal of Fashion Business
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• v.20 no.4
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• pp.153-171
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• 2016

With the advent of smart clothing for health care and sports, the sophisticated designs with curved seams are drawing attention. One of the problems in those clothing is to determine the design curves in 2D pattern, such that it corresponds to the lines on the intended 3D body. Moreover, the difficulty increases when the original pattern needs to be changed for various sizes and body types. We compare two methods of pattern enlargement in this paper: one is the offset/projection type, and the other is the split grading type. For the enlarged pattern with offset/projection type, the 3D surface offset was first adopted to transform the standard lower body to the target larger size; next, the design lines were projected to the new 3D surface, following which the 3D pattern was developed from the newly transformed 3D surface. In the second method, the enlarged pant patterns were developed by the split grading method. Here, a 3D pattern was developed from the initial body, and then enlarged to the target size by the conventional split grading method. Two feminine pants patterns were examined by 3D virtual fitting. We observed that the 3D offset/projection pants pattern was well fitted, having an evenly distributed surplus, as compared with the sample developed using the split grading method. The difference between the two patterns were apparent at the location where several curved lines merged.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1341-1348
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• 2012

In this paper, an efficient scheme for correcting rotated objects in medical images using the Mojette transform is presented. The Mojette transform is a kind of discrete Radon transform, where the transform domain is represented by a set of projections. The Mojette transform currently studied in the image compression area is modified for detecting the rotation angle of objects in medical images. First, in order to find accurate rotation angle, the projection value in the Mojette transform is determined by using pixels on the projection line and in addition the linear interpolation of pixels adjacent to the line. Second, at each projection angle, only one projection is implemented for reducing the amount of the calculation in the process of the Mojette transform. Finally, the projection in the Mojette transform is carried out at the predetermined ROI(Region Of Interest) at which the objects are not cropped or added by rotating the image. The simulation results show that the proposed method has good performance for correcting the rotation angle in medical images.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.181-193
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• 2010

The paper presents an alternative way to classical stereocorrelation. First, 2D image processing of random patterns is described. Sub-pixel displacements are determined using phase analysis. Then distortion evaluation is presented. The distortion is identified without any assumption on the lens model because of the use of a grid technique approach. Last, shape measurement and shape variation is caught by fringe projection. Analysis is based on two pin-hole assumptions for the video-projector and the camera. Then, fringe projection is coupled to in-plane displacement to give rise to 3D measurement set-up. Metrological characterization shows a resolution comparable to classical (stereo) correlation technique ($1/100^{th}$ pixel). Spatial resolution seems to be an advantage of the method, because of the use of temporal phase stepping (shape measurement, 1 pixel) and windowed Fourier transform (in plane displacements measurement, 9 pixels). Two examples are given. First one is the study of skin properties; second one is a study on leather fabric. In both cases, results are convincing, and have been exploited to give mechanical interpretation.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.111-117
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• 2010

A three-dimensional numerical model is employed to investigate wave deformation due to a submerged structure. The three-dimensional numerical model solves the spatially averaged Navier-Stokes equations for two-phase flows. The LES(large-eddy-simulation) approach is adopted to model the turbulence effect by using the Smagorinsky SGS(sub-grid scale) closure model. The two-step projection method is employed in the numerical solutions, aided by the Bi-CGSTAB technique to solve the pressure Poisson equation for the filtered pressure field. The second-order accurate VOF(volume-of-fluid) method is used to track the distorted and broken free surface. A simple linear wave is generated on a constant depth and compared with analytical solutions. The model is then applied to study wave deformation due to a submerged structure and the predicted results are compared with available laboratory measurements.