• Title/Summary/Keyword: 에지함수

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An Edge Linking Technique using a Modified Cellular Neural Networks (수정된 셀룰러 신경망을 이용한 에지 연결기법)

  • 김호준
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.292-294
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    • 2002
  • 본 연구에서는 영상에서 효과적인 에지 연결(edge linking)을 위하여 기존의 셀룰러 신경망 구조에서 두 가지 유형의 시냅스 구조를 고려한 활성화 특성을 제안한다 제시하는 모델에서 노드들간의 측면 연결에 의한 상호 작용은 노이즈에 의한 에지 및 영상에서 추출된 비최대점(non-maximum)의 에지를 억제할 문만 아니라, 특정 노드의 원형 이웃(circular neighborhood)으로 그려되는 특징들 간의 상호 연관도를 반영하여 에지의 연결 효과를 이를 수 있게 한다. 이러한 과정은 에지를 표현하는 벡터형식의 각 성분에 대한 활성화 특성으로부터 정형화된 에너지 함수로 모델링하고 이에 대한 최적화 과정으로써 구현될 수 있다.

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Three-Dimensional Vibration Analysis of Solid Cylinders of N-Sided Polygonal Cross-Section Having V-notches or Sharp Cracks (V노치 및 예리한 균열을 갖는 N 다변형 단면 입체 실린더의 3차원 진동해석)

  • Kim, Joo Woo
    • Journal of Korean Society of Steel Construction
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    • v.21 no.4
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    • pp.433-442
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    • 2009
  • In this paper, new three-dimensional vibration data for the solid cylinders of the N-sided polygonal cross-section with V-notches or sharp cracks are presented, and a Ritz procedure is employed, which incorporates a mathematically complete set of algebraic-trigonometric polynomials in conjunction with an admissible set of edge functions that explicitly model the tri-axial stress singularities that exist along a terminus edge of the V-notch. Convergence studies demonstrate the necessity of adding the edge functions to achieve the accurate frequencies and mode shapes of N-sided polygonal cylindrical solids with stress singularities.

A study on Wavelet function for Improved Edge Detection Properties (개선된 에지검출 특성을 위한 웨이브렛 함수에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.197-200
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    • 2007
  • Edge representing the boundary between two regions with the large brightness difference in image includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge in according to duration time and the amplitude of brightness variation, and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

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A Study on Edge Detection Algorithm using Grey Level Converting Function (그레이 레벨 변환 함수를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.921-923
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    • 2015
  • Edge in the image includes the size, direction and location of objects. The existing detection methods for detecting this edge is a method using Sobel, Prewitt, Roberts and Laplacian, etc. These existing methods use a fixed weighted mask in order to detect the edge and have somewhat insufficient edge detection characteristics. Therefore in this paper, an algorithm that detects the edge by applying the grey level converting function according to the pixel distribution of local mask was proposed.

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A Study on Wavelet Function for Improved Edge Detection Properties (개선된 에지검출 특성을 위한 웨이브렛 함수에 관한 연구)

  • Bae, Sang-Bum;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.6
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    • pp.1156-1161
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    • 2007
  • Edge representing the boundary between two regions with the large briskness difference in mage includes diverse information about object. Therefore, this information has been utilized in fields such as image segmentation and object recognition. There are many kinds of edge according to duration time and the amplitude of brightness variation and edge is generally detected through the differential. Recently, in fields of image processing and computer vision, edge detection methods have been proposed to use in specific applications. Hence, in this paper the wavelet function for improved edge detection properties was proposed and detected line-edge components of images and its performance was proven through simulations.

디지털 자동초점 시스템을 위한 초점 불완전 열화 추정과 복원 기법

  • 김상구;백준기
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1997.11a
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    • pp.139-143
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    • 1997
  • 본 논문에서는 점확산함수(point spread function; PSF)의 추정을 기반으로 한 완전한 자동초점 시스템을 제안한다. 초점이 맞지 않은 영상의 정확한 PSF의 추정을 위해서, 입력 영상을 부영상으로 분할하고, 에지를 가진 부영상들의 계수함수 응답의 평균을 취한다. 초점이 맞지 않은 열화로 발생하는 PSF는 보통 영상이 물체와 배경간에 선형의 경계를 가지고 있다는 가정하에 에지의 방향을 따라 평균되어진 계단함수 응답의 차이를 따라 추정되어진다. 이렇게 예측된 PSF를 사용하여 영상복원 필터는 제한적 최소 제곱의 접근방법을 통해 구현되어진다.

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Effective Silhouette Edge Rendering using Parameterized Brush Functions (파라미터화된 브러쉬 함수를 이용한 효과적인 실루엣 에지 렌더링)

  • 조진화;김성수;양태천
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10b
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    • pp.487-489
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    • 2000
  • 3차원 모델을 바탕으로 실루엣 에지를 찾아 디스플레이 해주는 대부분의 시스템들은 삼각 메쉬를 기반으로 한 모델 표현법을 사용하고 있다. NPR(nonphotorealistic rendering)에서 가장 초점을 두는 것은 컴퓨터로 렌더링된 결과가 사람이 그린듯한 효과를 줄 수 있느냐에 있다. 기존에 연구된 대부분의 시스템들은 사람이 그린듯한 효과를 주기 위해 물체의 표면에 대한 텍스츄어(Texture)와 어두운 정도, 그리고 스트록(Stroke)을 표면의 윤곽에 맞도록 그리는 많은 기법들을 소개해 왔다. 본 논문에서는 NPR 표현의 가장 기본이 되는 실루엣 에지 추출에 초점을 두고 추출한 실루엣 에지에 대해 파라미터화된 브러쉬 함수(Parameterized Brush Functions)를 적용하여 다양한 스타일로 디스플레이할 수 있는 기법을 제시한다.

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Image Compression and Edge Detection Based on Wavelet Transforms (웨이블릿 기반의 영상 압축 및 에지 검출)

  • Jung il Hong;Kim Young Soon
    • Journal of Korea Multimedia Society
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    • v.8 no.1
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    • pp.19-26
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    • 2005
  • The basis function of wavelet transform used in this paper is constructed by using lifting scheme, which is different from general wavelet transform. Lifting scheme is a new biorthogonal wavelet con-structing method, that does not use Fourier transform for constructing its basis function. In this paper, an image compression and reconstruction method using the lifting scheme was proposed. And this method improves data visualization by supporting a partial reconstruction and a local reconstruction. Approx- imations at various resolutions allow extracting various sizes of feature from an image or signal with a small amount of original information. An approximation with small size of scaling coefficients gives a brief outline of features at fast. Image compression and edge detection techniques provide good frame- works for data management and visualization in multimedia database.

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A Studyon Implementation of Edge Detection Algorithms Based on fuzzy Membership Models (퍼지모델을 기반으로한 에지검출 알고리즘 구현에관한 연구)

  • Lee, Bae-Ho;Kim, So-Yeon;Kim, Kwang-Hee
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.9
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    • pp.2447-2456
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    • 1998
  • Edge detection in the presence of noise is a well-known problem. this pper atempts to implement edge detection algorithms using fuzzy reasoning of fuzzy membership models. It examines an application-motived approach for solving the problem. Our approach is divided into three stages; fitering, segmentation and tracing. Filtering removes the noise from the original image and segmentation determines the edges and deects them. Finally, tracing assembles the edges into the related structure. Proposed method can be used effectively on these procedures by using fuzzy reasoning based on fuzzy models. In is compared with the previous edge detectio algorithms with fvorable results. Simulation results of the research are presented and discussed.

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An Edge Detector by Using Perfect Sharpening of Ramps (램프의 완전 선명화를 이용한 에지 검출기)

  • Lee, Jong-Gu;Yoo, Cheol-Jung;Chang, Ok-Bae
    • Journal of KIISE:Software and Applications
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    • v.34 no.11
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    • pp.961-970
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    • 2007
  • Since the usual conventional edge detectors employ the local differential derivatives, the detected edges are not uniform in their widths or some edges are missed out of the detection on magnified images. We employ a mapping from the exactly monotonic intensity distributions of ramp edges to the simple step functions of intensity, which is referred to as perfect sharpening map of ramp edges. This map is based on the non-local feature of intensity distribution and used to introduce a modified differentiation, in terms of which we can construct an efficient edge detector adaptive to the variation of edge width. By adopting the operator MADD in this paper, we developed an edge detector that works stably against the magnification of image or the variation of edge width. It is shown by comparing to the conventional algorithms that the proposed one is very excellent.