• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5036-5041
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• 2010

This paper introduces the complex-version of an Euclidean distance minimization algorithm based on a set of delta functions. The algorithm is analyzed to be able to compensate inherently the channel phase distortion caused by inferior complex channels. Also this algorithm has a relatively small size of Gaussian kernel compared to the conventional method of using a randomly generated symbol set. This characteristic implies that the information potential between desired symbol and output is higher so that the algorithm forces output more strongly to gather close to the desired symbol. Based on 16 QAM system and phase distorted complex-channel models, mean squared error (MSE) performance and concentration performance of output symbol points are evaluated. Simulation results show that the algorithm compensates channel phase distortion effectively in constellation performance and about 5 dB enhancement in steady state MSE performance.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1255-1262
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• 2004

This paper proposes a pattern matching algorithm which is useful for pattern matching and verification of images which includes noises. This algorithm is based on the feature that the signal energy of image is concentrated in a small frequency region in Fourier domain. The proposed method extracts the small parts around origins and compares the regions. Specifically, the parts around origins are extracted and subtracted, and finally experimental threshold is adopted for pattern matching. In particular, the proposed algorithm is useful for the images which includes noises because the noises are distributed in the high frequency region generally, and the method extracts the low frequency region only. Experimental result shows the method recognize ten standard images and three images includes various noises. This method shows the performance which is equal to or better than that of Phase Only Correlation in some cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2511-2520
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• 2011

This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.372-377
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• 2013

This paper have presented the breakdown voltage for double gate(DG) MOSFET. The analytical solution of Poisson's equation and Fulop's breakdown condition have been used to analyze for breakdown voltage. The double gate(DG) MOSFET has the advantage to reduce the short channel effects as improving the current controllability of gate. But we need the study for the breakdown voltage of DGMOSFET since the decrease of the breakdown voltage is unavoidable. To approximate with experimental values, we have used the Gaussian function as charge distribution for Poisson's equation, and the change of breakdown voltage has been observed for device geometry. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. As a result to observe the breakdown voltage, the smaller channel length and the higher doping concentration become, the smaller the breakdown voltage becomes. Also we have observed the change of the breakdown voltage for gate oxide thickness and channel thickness.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.34-45
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• 2005

In this paper, a novel implementation of a person verification system based on depth-weighted Hausdorff distance (DWHD) using the surface curvature of the face is proposed. The definition of Hausdorff distance is a measure of the correspondence of two point sets. The approach works by finding the nose tip that has a protrusion shape on the face. In feature recognition of 3D face image, one has to take into consideration the orientated frontal posture to normalize after extracting face area from original image. The binary images are extracted by using the threshold values for the curvature value of surface for the person which has differential depth and surface characteristic information. The proposed DWHD measure for comparing two pixel sets were used, because it is simple and robust. In the experimental results, the minimum curvature which has low pixel distribution achieves recognition rate of 98% among the proposed methods.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1273-1280
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• 2013

The UKF algorithm for tracking moving objects has fast convergence speed and good tracking performance without the derivative computation. However, this algorithm has serious drawbacks which limit its use in conditions such as Gaussian noise distribution. Meanwhile, the particle filter(PF) is a state estimation method applied to nonlinear and non-Gaussian systems without these limitations. But this method also has some disadvantages such as computation increase as the number of particles rises. In this paper, we propose the Unscented Particle Filter (UPF) algorithm which combines Unscented Kalman Filter (UKF) and Particle Filter (PF) in order to overcome these drawbacks.The performance of the UPF algorithm was tested to compare with Particle Filter using a 2-DOF (Degree of Freedom) Pendulum System. The results show that the proposed algorithm is more suitable to the nonlinear and non-Gaussian state estimation compared with PF.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.67-78
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• 2005

We proposed a blind watermarking for 3D mesh model using the patch CEGIs. The CEGI is the 3D orientation histogram with complex weight whose magnitude is the mesh area and phase is the normal distance of the mesh from the designated origin. In the proposed algorithm we divide the 3D mesh model into the number of patch that determined adaptively to the shape of model and calculate the patch CEGIs. Some cells for embedding the watermark are selected according to the rank of their magnitudes in each of patches after calculating the respective magnitude distributions of CEGI for each patches of a mesh model. Each of the watermark bit is embedded into cells with the same rank in these patch CEGI. Based on the patch center point and the rank table as watermark key, watermark extraction and realignment process are performed without the original mesh. In the rotated model, we perform the realignment process using Euler angle before the watermark extracting. The results of experiment verify that the proposed algorithm is imperceptible and robust against geometrical attacks of cropping, affine transformation and vertex randomization as well as topological attacks of remeshing and mesh simplification.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.157-163
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• 2013

In this paper, we propose a human detection technique using thermal imaging camera. The proposed method is useful at night or rainy weather where a visible light imaging cameras is not able to detect human activities. Under the observation that a human is usually brighter than the background in the thermal images, we estimate the preliminary human regions using the statistical confidence measures in the gray-level, brightness histogram. Afterwards, we applied Gaussian filtering and blob labeling techniques to remove the unwanted noise, and gather the scattered of the pixel distributions and the center of gravities of the blobs. In the final step, we exploit the aspect ratio and the area on the unified object region as well as a number of the principal components extracted from the object region images to determine if the detected object is a human. The experimental results show that the proposed method is effective in environments where visible light cameras are not applicable.