• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.4 s.107
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• pp.393-399
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• 2006

In this paper we applied a ray tracing method to estimate the scattering characteristics from large scale random rough surfaces. For the electromagnetic field evaluation, we have used the diffracted coefficient of the knife edge diffraction for the diffracted rays and Fresnel's reflection coefficients in connection with reflected rays. In addition, we examine to search for the traced rays using the imaging method which can be obtained all rays to arrived at receivers accurately and the diffracted field from rough surfaces is considered. Numerical examples have been carried out for the scattering characteristics of an ocean wave-like rough surface and delay spread characteristics of a building-like surface. In the present work we have demonstrated that the ray tracing method is effective to numerical analysis of a rough surface scattering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.533-535
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• 2018

As the use frequency of electronic communication equipment increases due to the influence of the 4th industrial revolution, the importance of image and signal processing is increasing. However, due to noise caused by various causes, the reliability of the equipment is degraded and malfunctions are caused. In this paper, we propose an algorithm to remove AWGN in most environments. The existing methods show relatively poor performance due to the smoothing phenomenon at the boundary of the image. To overcome this problem, we proposed a filter algorithm that adapts to the boundary region using the Sobel edge detection to remove the noise. And using the PSNR compared with traditional methods, such as to demonstrate the performance of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1696-1705
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• 1996

The theory of stack filtering, which is a generalization of median filtering, is used to the detection of intensity edges in noisey images. The proposed approach, called the Difference of Estimates(DoE) approach, is a new formulation of a morphological scheme which has been very sensitive to impulse noise. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates yields the binary edge map. We find that this approach yields results comparable to those obtained with the Canny operator for images with additive Gaussian noise, burt works much better when the noise is impulsive.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.327-335
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• 2003

Cellular Automata is discrete dynamical systems which natural phenomena may be specified completely in terms of local relation. In this Paper we Propose noise removal and edge detection algorithm using a Potts Automata which is based on Cellular Automata. The proposed method is aimed to locally increase or decrease the differences in gray level values between pixel of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is determined by Lyapunov operators for sequential and parallel update. We have found that proposed automata rules Present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuses the advantage and efficiency.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2814-2818
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• 2000

This paper describes an image processing algorithm capable of recognizing the road lane using a CDF (Cumulative Distribution Function). which is designed for the model function of the road lane. The CDF has distinctive peak points at the vicinity of the lane direction because of the directional and positional continuities of the lane. We construct a scatter diagram by collecting the edge pixels with the direction corresponding to the peak point of the CDF and carry out the principal axis-based line fitting for the scatter diagram to obtain the lane information. As noises play the role of making a lot of similar features to the lane appear and disappear in the image we introduce a recursive estimator of the function to reduce the noise effect and a scene understanding index (SUI) formulated by statistical parameters of the CDF to prevent a false alarm or miss detection. The proposed algorithm has been implemented in a real time on the video data obtained from a test vehicle driven in a typical highway.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.5
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• pp.415-427
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• 1987

This paper presents an experimental model-based vision system which can identify and locate objects in scenes containing multiple occluded parts. The objects are assumed to be rigid and planar parts. In any recognition system the-type of objects that might appear in the image dictates the type of knowledge that is needed to recognize the object. The data is reduced to a sequential list of points or pixels that appear on the boundary of the objects. Next the boundary of the objects is smoothed using a polygonal approximation algorithm. Recognition cosists in finding the prototype that matches model to image. Now the hidden edge is reconstructed by transition model objects into occluded objects. The best match is obtained by optimising some similarity measure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.225-230
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• 2011

In this paper, we propose the segmentation method for detecting the facial region by using watershed based on depth information and merge algorithm. The method consists of three steps: watershed segmentation, seed region detection, and merge. The input color image is segmented into the small uniform regions by watershed. The facial region can be detected by merging the uniform regions with chromaticity and edge constraints. The problem in the existing method using only chromaticity or edge can solved by the proposed method. The computer simulation is performed to evaluate the performance of the proposed method. The simulation results shows that the proposed method is superior to segmentation facial region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.124-131
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• 2007

This paper presents a block loss recovery technique for the image block data corrupted by transmission losses through the employment of fine directional interpolation (FDI). The proposed algorithm introduces a spatial direction vector (SDV). The SDVs are extracted from the edge information of the neighboring image data. Subsequently, the SDVs are adaptively applied to interpolate lost pixels on a pixel-by-pixel basis. This approach improves the capability to more reliably recover high-detailed contents in the corrupted block. Experimental results demonstrate that the FDI method performs better as compared to previous techniques.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2558-2562
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• 1999

This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.694-696
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• 2017

Image processing is being hailed as an important field with various applications as the digital information era advances. In particular, studies on methods to remove noise from images are being actively undertaken. This paper suggests an image restoration filter that processes through a weighted filter in accordance with the direction of partial masks to preserve edge while replacing the noise in the images with neighboring pixels. The PSNR(peak signal to noise ratio) was used as a tool to objectively judge the improvement effects compared to existing methods.