• Title/Summary/Keyword: Image Edge

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Image Retrieval Using Edge-based Variable Block DC (에지 기반 가변 블록 DC를 이용한 영상 검색)

  • 김동우;서은주;장언동;안재형
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05c
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    • pp.268-271
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    • 2002
  • 현재 우리가 접하는 영상은 모양, 색상, 질감 등의 성분을 이용한 검색 방법이 필요하다. 이중 질감 특성을 고려한 DC 영상 검색 기법은 구현이 간단하고 검색이 빠른 장점이 있다. 특히 블록을 가변으로 하였을 경우 검색 속도와 정확성을 효율적으로 높일 수 있다. 그러나 기존의 방법은 가변 블록을 하기 위하여 단순히 이진 영상을 가지고 객체 유무를 판단하므로 객체 영역 판단의 정확성이 낮아지고, 계산량이 많아지는 단점이 있다. 이러한 문제점을 해결하기 위해 객체 영역 판단에 에지를 이용하는 방법을 제안한다. 제안한 방법의 경우 객체 영역 판단의 정확성을 높이고 계산량을 줄일 수 있다.

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Lung image segmentation by watershed transform (워터쉐드 변형을 이용한 폐 영상 분할)

  • 김희숙;탁정남;이귀상;김수형;홍성훈
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.763-765
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    • 2004
  • 현재 의료 영상을 이용한 신속하고 정확한 진단과 치료를 위하여 각 기관별로 영상을 분할하는 방식이 기본적으로 사용되고 있다. 본 논문에서는 워터쉐드(Watershed) 알고리즘을 이용하여 해부학적 기관 중 폐 영역을 분할하는 방식을 제안한다. 초기에 소벨 에지 마스크(Sobel Edge Mask)를 이용하여 윤곽선을 강조하여 워터쉐드 알고리즘을 적용하였을 경우 과다 분할되는 문제점이 발생한다. 이를 해결하기 위하여 제거(Opening) 연산과 채움(Closing) 연산을 이용하여 마커(Marker) 정보를 추출하여 워터쉐드 알고리즘을 재적용하여 폐 영역 이미지를 분할하였다. 본 논문에서 제안한 마커 정보를 이용한 워터쉐드 재적용 방식은 폐 영역 효율적이고 정확하게 추출한다.

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Rule-based OPC and ORC Approach for Metal and Contact Layer Patterning (Metal과 Contact Layer Patterning을 위한 규칙기반 OPC 및 ORC Approach)

  • 이미영;이우희;이준하;이흥주
    • Proceedings of the KAIS Fall Conference
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    • 2003.06a
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    • pp.239-242
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    • 2003
  • Scale down으로 인해 부족해진 overlay margin을 통해 충분히 확보해주고, 이와 동시에 attPSM(attenuated phase shift)의 사용으로 발생하는 side-lobe 현상을 억제하기 위한 방법으로 rule-based OPC(optical proximity correction)룰 사용하여 side-lobe만을 효과적으로 추출한 후, 그 자리에 scattering bar를 삽입하였다. 그리고 ORC(optical rule checking)를 통해 original layout과 aerial image의 EPEs(edge placement errors)를 검사하여 검증에 걸리는 시간을 감소시켰다.

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Comparison Study of Image Quality of Direct and Indirect Conversion Digital Mammography System (직접 및 간접변환 방식의 디지털 유방 X선 촬영시스템의 영상화질 비교 연구)

  • Park, Hye-Suk;Oh, Yu-Na;Jo, Hee-Jeong;Kim, Sang-Tae;Choi, Yu-Na;Kim, Hee-Joung
    • Progress in Medical Physics
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    • v.21 no.3
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    • pp.239-245
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    • 2010
  • The purpose of this study is to comprehensively compare and evaluate the characteristics of image quality for digital mammography systems which use a direct and indirect conversion detector. Three key metrics of image quality were evaluated for the direct and indirect conversion detector, the modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), which describe the resolution, noise, and signal to noise performance, respectively. DQE was calculated by using a edge phantom for MTF determination according to IEC 62220-1-2 regulation. The contrast to noise ratio (CNR) was evaluated according to guidelines offered by the Korean Institute for Accreditation of Medical Image (KIAMI). As a result, the higher MTF and DQE was measured with direct conversion detector compared to indirect conversion detector all over spatial frequency. When the average glandular dose (AGD) was the same, direct conversion detector showed higher CNR value. The direct conversion detector which has higher DQE value all over spatial frequency would provide the potential benefits for both improved image quality and lower patient dose in digital mammography system.

Application of Image Processing Techniques to GPR Data for the Reliability Improvement in Subsurface Void Analysis (지표레이더(GPR) 탐사자료를 이용한 지하공동 분석 시 신뢰도 향상을 위한 영상처리기법의 활용)

  • Kim, Bona;Seol, Soon Jee;Byun, Joongmoo
    • Geophysics and Geophysical Exploration
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    • v.20 no.2
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    • pp.61-71
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    • 2017
  • Recently, ground-penetrating radar (GPR) surveys have been actively carried out for precise subsurface void investigation because of the rapid increase of subsidence in urban areas. However, since the interpretation of GPR data was conducted based on the interpreter's subjective decision after applying only the basic data processing, it can result in reliability problems. In this research, to solve these problems, we analyzed the difference between the events generated from subsurface voids and those of strong diffraction sources such as the buried pipeline by applying the edge detection technique, which is one of image processing technologies. For the analysis, we applied the image processing technology to the GRP field data containing events generated from the cavity or buried pipeline. As a result, the main events by the subsurface void or diffraction source were effectively separated using the edge detection technique. In addition, since subsurface voids associated with the subsidence has a relatively wide scale, it is recorded as a gentle slope event unlike the event caused by the strong diffraction source recorded with a sharp slope. Therefore, the directional analysis of amplitude variation in the image enabled us to effectively separate the events by the subsurface void from those by the diffraction source. Interpretation based on these kinds of objective analysis can improve the reliability. Moreover, if suggested techniques are verified to various GPR field data sets, these approaches can contribute to semiautomatic interpretation of large amount of GPR data.

Improvement of Disparity Map using Loopy Belief Propagation based on Color and Edge (Disparity 보정을 위한 컬러와 윤곽선 기반 루피 신뢰도 전파 기법)

  • Kim, Eun Kyeong;Cho, Hyunhak;Lee, Hansoo;Wibowo, Suryo Adhi;Kim, Sungshin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.5
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    • pp.502-508
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    • 2015
  • Stereo images have an advantage of calculating depth(distance) values which can not analyze from 2-D images. However, depth information obtained by stereo images has due to following reasons: it can be obtained by computation process; mismatching occurs when stereo matching is processing in occlusion which has an effect on accuracy of calculating depth information. Also, if global method is used for stereo matching, it needs a lot of computation. Therefore, this paper proposes the method obtaining disparity map which can reduce computation time and has higher accuracy than established method. Edge extraction which is image segmentation based on feature is used for improving accuracy and reducing computation time. Color K-Means method which is image segmentation based on color estimates correlation of objects in an image. And it extracts region of interest for applying Loopy Belief Propagation(LBP). For this, disparity map can be compensated by considering correlation of objects in the image. And it can reduce computation time because of calculating region of interest not all pixels. As a result, disparity map has more accurate and the proposed method reduces computation time.

Accelerated Convolution Image Processing by Using Look-Up Table and Overlap Region Buffering Method (Loop-Up Table과 필터 중첩영역 버퍼링 기법을 이용한 컨벌루션 영상처리 고속화)

  • Kim, Hyun-Woo;Kim, Min-Young
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.4
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    • pp.17-22
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    • 2012
  • Convolution filtering methods have been widely applied to various digital signal processing fields for image blurring, sharpening, edge detection, and noise reduction, etc. According to their application purpose, the filter mask size or shape and the mask value are selected in advance, and the designed filter is applied to input image for the convolution processing. In this paper, we proposed an image processing acceleration method for the convolution processing by using two-dimensional Look-up table (LUT) and overlap-region buffering technique. First, based on the fixed convolution mask value, the multiplication operation between 8 or 10 bit pixel values of the input image and the filter mask values is performed a priori, and the results memorized in LUT are referred during the convolution process. Second, based on symmetric structural characteristics of the convolution filters, inherent duplicated operation region is analysed, and the saved operation results in one step before in the predefined memory buffer is recalled and reused in current operation step. Through this buffering, unnecessary repeated filter operation on the same regions is minimized in sequential manner. As the proposed algorithms minimize the computational amount needed for the convolution operation, they work well under the operation environments utilizing embedded systems with limited computational resources or the environments of utilizing general personnel computers. A series of experiments under various situations verifies the effectiveness and usefulness of the proposed methods.

Analysis of size distribution of riverbed gravel through digital image processing (영상 처리에 의한 하상자갈의 입도분포 분석)

  • Yu, Kwonkyu;Cho, Woosung
    • Journal of Korea Water Resources Association
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    • v.52 no.7
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    • pp.493-503
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    • 2019
  • This study presents a new method of estimating the size distribution of river bed gravel through image processing. The analysis was done in two steps; first the individual grain images were analyzed and then the grain particle segmentation of river-bed images were processed. In the first part of the analysis, the relationships (long axes, intermediate axes and projective areas) between grain features from images and those measured were compared. For this analysis, 240 gravel particles were collected at three river stations. All particles were measured with vernier calipers and weighed with scales. The measured data showed that river gravel had shape factors of 0.514~0.585. It was found that the weight of gravel had a stronger correlation with the projective areas than the long or intermediate axes. Using these results, we were able to establish an area-weight formula. In the second step, we calculated the projective areas of the river-bed gravels by detecting their edge lines using the ImageJ program. The projective areas of the gravels were converted to the grain-size distribution using the formula previously established. The proposed method was applied to 3 small- and medium- sized rivers in Korea. Comparisons of the analyzed size distributions with those measured showed that the proposed method could estimate the median diameter within a fair error range. However, the estimated distributions showed a slight deviation from the observed value, which is something that needs improvement in the future.

An Automatic ROI Extraction and Its Mask Generation based on Wavelet of Low DOF Image (피사계 심도가 낮은 이미지에서 웨이블릿 기반의 자동 ROI 추출 및 마스크 생성)

  • Park, Sun-Hwa;Seo, Yeong-Geon;Lee, Bu-Kweon;Kang, Ki-Jun;Kim, Ho-Yong;Kim, Hyung-Jun;Kim, Sang-Bok
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.3
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    • pp.93-101
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    • 2009
  • This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.

Estimation of Incident Detection Time on Expressways Based on Market Penetration Rate of Connected Vehicles (커넥티드 차량 보급률 기반 고속도로 돌발상황 검지시간 추정)

  • Sanggi Nam;Younshik Chung;Hoekyoung Kim;Wonggil Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.38-50
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    • 2023
  • Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.