• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.79-86
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• 2004

In the integration of Sommerfeld type for space domain Green's function, a accurate closed-from Green's function method provides more exact solution than the typical complex image method and two-level method. The accurate closed-form Green's function method is applied to obtain the space domain Green's functions of planar structures with general sources. Please put the abstract of paper here.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.346-354
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• 2007

Interpolation methods to get the magnified image from an image with low resolution use known pixels to make an interpolated pixel. This interpolation process usually generates blurred edges and blocking effect in the result image. To improve these defects, conventional methods multiply proper weights reflecting neighborhood pixels and add the values during interpolating process. The proposed method changes input pixels in consideration of information of neighborhood pixels, gets interpolated pixels by using these values and improves the quality of interpolated image. Firstly, we compute difference values of the diagonal directions of a pixel and classify flat regions and complex regions according to these values. If the regions is complex ones, the proposed method changes an original pixel into a new value using a input pixel and a median value of it's neighbor pixels. Therefore, the proposed method applies bilinear method to the original pixels in flat regions and the changed ones in complex regions and produces the interpolated images. We evaluate the performance of the proposed method with existing methods by using PSNR and the quality of enlarged image. The results show that the proposed method improves PSNR in comparing with conventional methods and that is superior to the existing methods in terms of the quality of the interpolated image.

• Journal of Korea Game Society
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• v.7 no.1
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• pp.43-52
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• 2007

This article describes a new contribution culling method for fast rendering of complex huge urban scenes. A view frustum culling technique is used for fast rendering of complex scenes. To support the levels-of-detail, we subdivide the image regions and construct a weighted quadtree. Only visible objects at the current camera position contributes the current quadtree and the weight is assigned to each object in the quadtree. The weight is proportional to the image area of the projected object, so large buildings in the far distance are less likely to be culled out than small buildings in the near distance. The rendering time is nearly constant not depending on the number of visible objects. The proposed method has applied to a new metropolitan region which is currently under development. Experimental results showed that the rendering quality of the proposed method is barely distinguishable from the rendering quality of the original method, while the proposed method reduces the number of polygons by about 9%. Experimental results showed that the proposed rendering method is appropriate for real-time rendering applications of complex huge scenes.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.10
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• pp.507-512
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• 2001

Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, many researchers have been studying on extracting from color information, because of its advantages. This paper proposes a feature and its extraction method based on color information in an image. The proposed method is computed from the image segmented into two parts: the complex part and the plan part. Our experiments show that the performance of the proposed method is better as compared with the original color correlogram method.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.336-340
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• 2011

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2575-2586
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• 2000

In this paper, we propose an algorithm which can automatically extract the road information in a map image. The proposed method extracts the road image in the complex map image. The extracted image is converted into the skeleton image by thining method. The converted image contains various problems. In order to correct these problems, after the road is classified by the number of Rutovitz-connectivity which represents the characteristic of road, those are respectively corrected according to the load characteristic. In the simulation, the proposed method has obtained good results for the various type of map images.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1157-1160
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• 2005

The denoising and reconstruction of color images are increasingly studied in the field of computer vision and image processing. Especially, the denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noises on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps; training of canonical eigenface space using PCA, automatic extracting of face features using active appearance model, relighing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denosing method efficiently removes complex color noises on input face images.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.6
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• pp.557-562
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• 2009

Abrupt change of cross-section in mechanical parts is one of significant causes of structural fracture. In this paper, a hybrid method is employed to analyze the stress distribution of a discontinuous plate. The plate with an inclined crack is utilized in our experiment and the stress field in the vicinity of crack tip is calculated through isochromatic fringe order of given points. This calculation can be made handy through least-squares method integrated with complex power series representation(Laurent series) implemented on a computer program for high-speed processing. In order to accurately compare calculated results with experimental ones, both of actual and regenerated photoelastic fringe patterns are doubled and sharpened by digital image processing. The experiment results show that regenerated patterns obtained by hybrid method are quite comparable to actual patterns.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.4
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• pp.54-75
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• 1993

The purpose of this thesis is to suggest objective basic data for the super graphics in the urban landscape through the quantitative visual quality analysis. For this, the image structure of super graphics have been measured mainly by questionnaries and semantic differential scle method and analyzed by the method of factor analysis, means and multiple regression. Degree of visual preference have been measured mainly by questionnaries and likert attitude scale method and finaly these data have been analyzed by using the stepwise method. The data were collected by presenting 12 super graphics photographs-4 each sample pictures from the 3 each selected districts representing typical urban landscape style(central business district, shopping district, apartment complex). Observer groups were categorized as professionals, students, the others. Result of this thesis can be summarized as fallows: 1. From all 12(3${\times}$4) sample super graphics, the value of each semantic differential scale among the observer groups were presented significant group difference. But no significant difference of the S.D. scale value were observed among central business district, shopping district and apartment complex super graphics. 2. For all experimental points, 4 types of factor have been observed. Factors covering the image of super graphics were found to be the evaluation, the intimacy, the potentiality and the tidiness. 3. Main factors of the super graphics image and factors indicating the group variations yielded high significance between areas. 4. The harmony with surrounding environment, the proper selection of super graphics subject yielded high values for all groups. Especially, the good color sense with building was the most important variable determining the degree of visual preference. 5. The urban C.B.D. super graphics obtained 5∼12 ranks of regional visual preference and the shopping district super graphics obtained 2∼11 ranks, and apartment complex super graphics obtained 1∼7 ranks.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.432-440
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• 2007

In this paper, we propose a small target detection algorithm for FLIR image with complex background. First, we compute the motion information of target from the difference between the current frame and the created background image. However, the slow speed of target cause that it has the very low gray level value in the difference image. To improve the gray level value, we perform the local gamma correction for difference image. So, the detection index is computed by using statistical characteristics in the improved image and then we chose the lowest detection index a true target. Experimental results show that the proposed method has significantly the good detection performance.