• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.206-217
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• 2015

This paper presents a complete S-shape feed rate scheduling approach (CSFA) with confined jerk, acceleration and command feed rate for parametric tool path. For a Non-Uniform Rational B-Spline (NURBS) tool path, the critical points of the tool path where the radius of curvature reaches extreme values are found firstly. Then, the NURBS curve is split into several NURBS sub-curves or blocks by the critical points. A bidirectional scanning strategy with the limitations of chord error, normal/tangential acceleration/jerk and command feed rate is employed to make the feed rate at the junctions between different NURBS blocks continuous. To improve the efficiency of the feed rate scheduling, the NURBS block is classified into three types: short block, medium block and long block. The feed rate profile corresponding to each NURBS block is generated according to the start/end feed rates and the arc length of the block and the limitations of tangential acceleration/jerk. In addition, two compensation strategies are proposed to make the feed rate more continuous and the arc increment more precise. Once the feed rate profile is determined, a second-order Taylor's expansion interpolation method is applied to generate the position commands. Finally, experiments with two free-form NURBS curves are conducted to verify the applicability and accuracy of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.86-94
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• 2010

In this paper, we propose spatially adaptive color demosaicing of noisy Bayer data. When sensor noises are not considered in demosaicing, they may degrade result image. In order to obtain high resolution image, sensor noises are considered in the color demosaicing step. We identify flat, edge and pattern regions at each pixel location to improve the performance of the algorithm and to reduce complexity. Based on the pre-classified regions, the demosaicing of the G channel is performed using the local statistics to reduce the interpolation error. The sensor noise is simultaneously removed by a modified version of non-local mean filter in the green and in the color difference domain. The R and B channels are interpolated easily using fully interpolated and denoised G and color difference values. Experimental results show that the proposed method achieves a significant improvement in terms of visual and numerical criteria, when compared to conventional methods.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.255-262
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• 2007

This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, $YC_bC_r$, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.183-191
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• 2015

If the damage analysis on river-side facilities such as dam, river bank structures and bridges caused by disasters such as typhoon, flood, etc. becomes available, it can be a great help for disaster recovery and decision-making. In this research, We tried to extract a Digital Surface Model (DSM) and analyze the accuracy from Unmanned Air Vehicle (UAV) images on river-side facilities. We tried to apply stereo image-based matching technique, then extracted match results were united with one mosaic DSM. The accuracy was verified compared with a DSM derived from LIDAR data. Overall accuracy was around 3m of absolute and root mean square error. As an analysis result, we confirmed that exterior orientation parameters exerted an influence to DSM accuracy. For more accurate DSM generation, accurate EO parameters are necessary and effective interpolation and post process technique needs to be developed. And the damage analysis simulation with DSM has to be performed in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.232-237
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• 2010

In this paper, a slit light laser range finding method using perspective warping calibration is proposed. This approach has an advantage to acquire relatively high accuracy, although the optical system is nonlinear. In the calibration, we detect the calibration points which are marked on the calibration panel and acquire the center position of the slit light laser in the image, which are used for computing the real positions of the slit light by using perspective warping. A calibration file is obtained by integrating the calibration data with the transition of the panel. The range data is acquired by interpolating the center position of the slit light laser to the calibration coordinates. Experimental results show that the proposed method provides the accuracy of 0.08mm error in depth range of 130mm with the low cost optical system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.1036-1043
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• 2005

In this paper, we propose a sequential motion vector recovery algorithm for H.264 video coding standard. Motion vectors of H.264 video coding standard cover relatively smaller areas than other standard, since motion estimation of H.264 takes place in the fashion of variable block size. Therefore, the correlation of motion vectors between neighboring blocks increases as the block size of motion estimation is lowered. Under the framework of sequential recovery, we introduce a motion vector recovery using $\alpha$-trimed mean filter. Experimental results show that proposed algorithm is useful in real time video delivery .with nearly comparable or better visual quality than previous approaches such as macro block boundary matching and Lagrage interpolation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.2
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• pp.83-100
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• 1980

This study was intended to computerize the structural analysis of two-dimensional continuum by finite element method, and to provide a preparatory basis for more sophisticated and more generalized computer programs of this kind. A computer program, applicable to any shape of two-dimensional continuum, was formulated on the basis of 16-degree-of- freedom rectangular element. Various computational aspects pertaining to the implementation of finite element method were reviewed and settled in the course of programming. The validity of the program was checked through several case studies. To assess the accuracy and the convergence characteristics of the method, the results computed by the program were compared with solutions by other methods, namely the analytical Navier's method and the framework method. Through actual programming and analysis of the computed results, the following facts were recognized; 1) The stiffness matrix should necessarily be assembled in a condensed form in order to make it possible to discretize the continuum into practically adequate number of elements without using back-up storage. 2) For minimization of solution time, in-core solution of the equilibrium equation is essential. LDLT decomposition is recommended for stiffness matrices condensed by the compacted column storage scheme. 3) As for rectangular plates, the finite element method shows better performances both in the accuracy and in the rate of convergence than the framework method. As the number of elements increases, the error of the finite element method approaches around 1%. 4) Regardless of the structural shape, there is a uniform tendency in convergence characteristics dependent on the shape of element. Square elements show the best performance. 5) The accuracy of computation is independent of the interpolation function selected.