• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.393-396
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• 2000

본 논문에서는 영상의 화소값으로부터 추출된 유사 특징점(quasi-feature point)을 이용한 이미지 모자이킹 알고리즘을 제안한다. 유사 특징점의 선택은 전역 정합(global matching)의 결과로부터 중첩된 영역을 4개의 부영역(sub-area)으로 분할하고, 각각의 분할된 부 영역에서 국부 분산(local variance)의 크기가 큰 블록을 선정, 이 블록의 중심 화소를 유사 특징점으로 선택한다. 유사 특징점에 대한 정합은 카메라 이동에 따른 왜곡(distortion)과 조명의 변화를 고려한 블록 정합 알고리즘(block matching algorithm)을 이용한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.696-701
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• 2017

This paper proposes an improved de-interlacing method that converts interlaced images into progressive images from one field. First, it calculates inter-pixel values applying third-order spline interpolation for the horizontal direction from four upper lower pixel values of missing pixels. From inter-pixel values obtained from spline interpolation and upper lower pixels with value, the proposed method makes an accurate estimate of the direction by applying the correlation between upper and lower pixels. The correlation between upper and lower pixels is calculated in nine directions of a missing pixel by using values obtained from spline interpolation and pixels with value. The direction of an edge is determined as the direction in which the correlation between upper and lower pixels is at its minimum. Thus, a missing pixel is calculated by taking the average of upper lower pixels obtained from the predicted direction of an edge. From the simulation results, there are problems in that it takes a bit more time for processing, but it is expected that the time problem will be improved by increasing CPU processing speed. As for image quality, it is shown that the proposed method improves both subjective and objective image quality and quantitatively improves picture signal-to-noise ratio (PSNR) in the range between 0.1 dB to 0.5 dB, as compared with previously presented de-interlacing methods.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.55-68
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• 2012

In this paper, we propose a novel method to solve the problem of excessive segmentation out of the method of segmenting regions from an image using Homogeneity Threshold($H_T$). The algorithm of the previous image segmentation based on $H_T$ was carried out region growth by using only the center pixel of selected window. Therefore it was caused resulting in excessive segmented regions. However, before carrying region growth, the proposed method first of all finds out whether the selected window is homogeneity or not. Subsequently, if the selected window is homogeneity it carries out region growth using the total pixels of selected window. But if the selected window is not homogeneity, it carries out region growth using only the center pixel of selected window. So, the method can reduce remarkably the number of excessive segmented regions of image segmentation based on $H_T$. In order to show the validity of the proposed method, we carried out multiple experiments to compare the proposed method with previous method in same environment and conditions. As the results, the proposed method can reduce the number of segmented regions above 40% and doesn't make any difference in the quality of visual image when we compare with previous method. Especially, when we compare the image united with regions of descending order by size of segmented regions in experimentation with the previous method, even though the united image has regions more than 1,000, we can't recognize what the image means. However, in the proposed method, even though image is united by segmented regions less than 10, we can recognize what the image is. For these reason, we expect that the proposed method will be utilized in various fields, such as the extraction of objects, the retrieval of informations from the image, research for anatomy, biology, image visualization, and animation and so on.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1867-1873
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, an algorithm for detecting the edge is proposed by applying the cross mask based on the center pixel and up, down, left and right mask based on the surrounding pixels of center pixel in order to solve these problems. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.207-210
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• 1998

기존의 DPCM에 의한 압축방법은 예측오차를 양자화하여 전송한 후 복원하는 것으로 8레벨로 양자화하는 경우 3bpp의 비트율을 갖는다. 본 논문에서는 화소값의 압축에 의해 기존의 DPCM보다 예측오차값의 분포를 0을 중심으로 더 집중시킴으로써 더 낮은 비트율을 갖는 압축방법을 제안한다. 압축된 각 화소의 예측오차값은 DPAM방법에 의해 8-레벨로 양자화되고, 양자화된 예측오차의 열을 4와 2 단위로 분할하여 예측오차의 학습된 열로 구성된 각각의 코드북과 비교한다. 비교 결과 코드북의 주소를 생성하여 전송하고, 복원시 화소값을 확장한다. 제안된 방법은 DPCM방법보다 2.4~4.06dB 낮은 복원 영상의 화질을 보이지만, 비트율은 2.17~2.34bpp를 얻음으로써 0.66~0.83bpp정도 개선할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1383-1388
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• 2016

Although image signal processing is used in many fields, degradation takes place in the process of transmitting image data by several causes. CWMF, A-TMF, and AWMF are the typical methods to eliminate noises from image data damaged under salt and pepper noise environment. However, those filters are not effective for noise rejection under highly dense noise environment. In this respect, the present study proposed an algorithm to remove in salt and pepper noise. In case the center pixel is determined to be non-noise, it is replaced with original pixel. In case the center pixel is noise, it segments local mask into 4 directions and uses linear interpolation to estimate original pixel. And then it applies spatial weight to the estimated pixel. The proposed algorithm shows a high PSNR of 24.56[dB] for House images that had been damaged of salt and pepper noise(P = 50%), compared to the existing CWMF, A-TMF and AWMF there were improvements by 16.46[dB], 12.28[dB], and 12.32[dB], respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1844-1850
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• 2016

The bilateral filter can reduce the noise while preserving details computing the filtering output at each pixels as the average of neighboring pixels. In this paper, we propose a real-time system based on window division. Overall performance is increased due to the parallel architectures which computes five rows in the kernel window simultaneously but with pipelined scheduling. We consider the tradeoff between the filter performance and the hardware cost and the bit allocation has been determined by PSNR analysis. The proposed architecture is designed with verilogHDL and synthesized using Dongbu Hitek 110nm standard cell library. The proposed architecture shows 416Mpixels/s (397fps) of throughput at 416MHz of operating frequency with 132K gates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.989-995
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• 2022

Currently, the demand for image processing is increasing due to the development of IT technology, and active research is being conducted. Since image data generates image noise due to various external causes, and thus degrades the performance of the image, noise removal is essential. Salt and Pepper noise is a representative image noise, and various studies are being conducted to remove it. Existing algorithms include A-TMF, AFMF, LIWF, but these have the disadvantage that their performance is somewhat insufficient. Therefore, in this paper, we propose an algorithm that performs filtering using linear interpolation with effective pixels existing around the central pixel only in case of noise after performing noise judgment in order to efficiently remove salt and pepper noise. In order to judge the performance of the proposed algorithm, it was compared using the processed image of the previously studied algorithm and PSNR.

• Journal of Korean Classical Literature and Education
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• no.37
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• pp.185-215
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• 2018

This paper tried to interpret new phenomenon in the narrative focusing on the tale. People telling about this story understood it in the way of recognizing and resigning the power of powerful destiny. This article poses a problem to that point. The male character begins the question "why?" And experiences a process of thoughtful thought. And he finds out his past life and pioneers his destiny. The find past life in this tale, it means 'an opportunity to choose oneself and life for themselves'. This can be interpreted as Samsara of Buddhism that does not insist on a fixed self. Experience of this process of reasoning according to narrative context of folktale will become literary therapy activity confirming the effectiveness of marital conflict narrative including the former motifs.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.556-558
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• 2002

항공사진에 포함된 기점 마크의 방사 및 기하 특성을 이용하여 마크의 중심 위치를 자동으로 인식하기 위한 방안을 제안한다. 마크를 포함하는 배경 영역의 방사 특성에 기반을 푼 전략에 근거하여 입력된 영상을 이치화한 다음 형태 연산자를 적용시켜 기전 마크가 있는 후보 영역을 추출한다. 기하 특성에 기반을 둔 전략에 근거하여 ▽$^2$G 필터링과 대칭성 강조 필터링을 적용시킨 후, 대칭이 가장 강하게 나타나는 위치인 마크의 중심 위치를 구한다. 66매의 기점 마크 영상에 대한 평가 결과 중심 위치가 1 화소의 정확도까지 얻어질 수 있다는 것을 확인할 수 있었다.