• Title/Summary/Keyword: 에지검출

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Color Code Detection and Recognition Using Image Segmentation Based on k-Means Clustering Algorithm (k-평균 클러스터링 알고리즘 기반의 영상 분할을 이용한 칼라코드 검출 및 인식)

  • Kim, Tae-Woo;Yoo, Hyeon-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1100-1105
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    • 2006
  • Severe distortions of colors in the obtained images have made it difficult for color codes to expand their applications. To reduce the effect of color distortions on reading colors, it will be more desirable to statistically process as many pixels in the individual color region as possible, than relying on some regularly sampled pixels. This process may require segmentation, which usually requires edge detection. However, edges in color codes can be disconnected due tovarious distortions such as zipper effect and reflection, to name a few, making segmentation incomplete. Edge linking is also a difficult process. In this paper, a more efficient approach to reducing the effect of color distortions on reading colors, one that excludes precise edge detection for segmentation, was obtained by employing the k-means clustering algorithm. And, in detecting color codes, the properties of both six safe colors and grays were utilized. Experiments were conducted on 144, 4M-pixel, outdoor images. The proposed method resulted in a color-code detection rate of 100% fur the test images, and an average color-reading accuracy of over 99% for the detected codes, while the highest accuracy that could be achieved with an approach employing Canny edge detection was 91.28%.

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A Study on Edge Detection Algorithm using Local Mask and Morphological Operation (모폴로지 연산과 국부 마스크를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;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.900-902
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    • 2015
  • In the modern society, according to the advancement in digital image processing technology, edge detection is being utilized in various application sectors such as smart device and medical, etc. In existing edge detection methods, there are Sobel, Prewitt, Roberts and Laplacian, etc, which uses the mask. These previous methods are easy to implement but shows somewhat insufficient results. Therefore, in order to compensate the problems of existing methods, in this paper, an algorithm that detects the edge using the local mask and morphological operation was proposed and the detection performance was compared against the previous methods.

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Edge-based Surface Segmentation Algorithm of 3-D Image using Curvature (곡률을 이용한 3차원 영상의 에지 기반 표면 분할 알고리즘)

  • Seol, Seong-Uk;Lee, Jae-Chul;Nam, Gi-Gon;Jeon, Gye-Rok;Ju, Jae-Heum
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.2
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    • pp.199-207
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    • 2001
  • In this paper, we suggest an edge-based surface segmentation algorithm of 3D image using curvature. For the first, in this proposed method, we approximate 3D depth data to second order curves by each scan line and decide splitting points of 3D edges by curvature of the approximated curves. And finally make a group as 3D surface with the region of input image by the 3D edges. In the conventional algorithms, there are some difficulties in detecting 3D edge with the separated processes for the jump edge and the crease edge and especially, in deciding the ambiguous discontinuity of surface directions about the crease edge. The proposed algorithm decides curvature discontinuity using curvature which is simply calculated by a geometrical approximation. Furthermore, the algorithm has a cooperated process to calculate the jump and crease edges. The results of computer simulations with several 3D images show that the proposed method yields better performance as comparing with the conventional methods.

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Difference Edge Acquisition for B-spline Active Contour-Based Face Detection (B-스플라인 능동적 윤곽 기반 얼굴 검출을 위한 차 에지 영상 획득)

  • Kim, Ga-Hyun;Jung, Ho-Gi;Suhr, Jae-Kyu;Kim, Jai-Hie
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.6
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    • pp.19-27
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    • 2010
  • This paper proposes a method for enhancing detection performance and reducing computational cost when detecting a human face by applying B-spline active contour to the frame difference of consecutive images. Firstly, the method estimates amount of user's motion using kurtosis. If the kurtosis is smaller than a pre-defined threshold, it is considered that the amount of user's motion is insufficient and thus the contour fitting is not applied. Otherwise, the contour fitting is applied by exploiting the fact that the amount of motion is sufficient. Secondly, for the contour fitting, difference edges are detected by combining the distance transformation of the binarized frame difference and the edges of current frame. Lastly, the face is located by assigning the contour fitting process to the detected difference edges. Kurtosis-based motion amount estimation can reduce a computational cost and stabilize the results of the contour fitting. In addition, distance transformation-based difference edge detection can enhance the problems of contour lag and discontinuous difference edges. Experimental results confirm that the proposed method can reduce the face localization error caused by the contour lag and discontinuity of edges, and decrease the computational cost by omitting approximately 39% of the contour fitting.

Resuch to Lane detection Algorism Using Regression Analysis (직선회귀모형을 이용한 효율적인 차선 검출 알고리즘에 관한 연구)

  • Kang, Min-Seok;Cheong, Cha-Keon
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.288-289
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    • 2008
  • 이 논문은 차선의 경계가 있는 도로에서 촬영된 흑백영상에서 차선에 관한 정보를 찾아 검출하는 알고리즘을 제안한다. 영강을 블록 단위로 나누고 직선회귀모형(Linear Regression Analysis)을 사용하여 기울기와 y절편(intercept)을 구한다. 검출된 에지의 위치정보를 블록을 이용하여 다음 프레임에 보내고, 다음 프레임에서 에지의 위지정보와 y절편, 기울기를 이용해 계속 추적해 가는 방법을 통하여 검출의 정확도를 높이고자 하였다.

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Scene Classification in MPEG Compressed Soccer Video (MPEG 압축 영역에서 축구 비디오의 scene classification)

  • 김종민;황선규;김진웅;김희율
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.574-576
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    • 2001
  • 본 논문에서는 최근 관심이 증가하고 있는 축구 경기 MPEG 비디오에서 정면이 변하는 부분을 검출하고 동일한 의미의 장면들을 분류하는 기술을 제안한다. MPEG 비디오에서 디코딩 과정을 거치지 않고 직접 에지(edge) 정보와 색상 분포 정보를 추출하여 적은 연산량으로 장면 전환 검출의 정확성을 높이고, 검출된 결과를 기반으로 샷(shot)을 특징 지울 수 있는 특정 색상들과 에지 정보를 이용해서 축구 MPEG 비디오내의 장면들을 내용적으로 분류한다. 제안한 방법은 카메라 움직임으로 발생하는 글러벌 모션의 변화에 대해서도 효과적으로 장면 전환을 검출하고 의미적으로 유사한 샷들에 대하여 장면 분류를 수행하는 결과를 확인하였다.

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Detection of electrical power lines using edge direction (에지방향을 이용한 전력선 검출)

  • Kim, Dong-Wook;Kang, Jeong-Hyuck
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.04a
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    • pp.429-432
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    • 2010
  • 본 논문에서는 열 영상 기반의 전력선 검출을 위한 효과적인 방법을 제안하고자 한다. 제안된 방법에서는 전력선이 가지고 있는 방향 특성을 이용하여 전처리과정을 통해 에지의 방향을 추출하고 이를 기반으로 허프 변환(hough transform)을 이용하여 전력선을 검출한다. 모의실험을 통하여 이러한 전력선 검출 방법 매우 유효한 방법임을 확인할 수 있었다.

Effective scene change detection methods using characteristics of MPEG video (MPEG 비디오의 특성 추출을 이용한 효과적인 장면 전환 검출 기법)

  • 곽영경;최윤석;고성제
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.8B
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    • pp.1567-1576
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    • 1999
  • In this paper, we propose new methods to detect a scene cut and a dissolve region in compressed MPEG video sequences. The scene cut detection method uses edge images obtained using DCT AC coefficients and the dissolve detection method utilizes the macroblock type information of the MPEG stream. The proposed scene cut detection method is insensitive to brightness and can detect scene changes more precisely than the methods using DC coefficients since AC edge images can express original images more exactly than DC edge images do. The proposed dissolve detection method using the number of intra macroblocks(MBs) computationally efficient since it does not require the decoding process. Experimental results show that the proposed methods perform better in detection scene changes than conventional other methods.

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Face Detection in Near Infra-red for Human Recognition (휴먼 인지를 위한 근적외선 영상에서의 얼굴 검출)

  • Lee, Kyung-Sook;Kim, Hyun-Deok
    • Journal of Digital Contents Society
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    • v.13 no.2
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    • pp.189-195
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    • 2012
  • In this paper, face detection method in NIR(Near-InfraRed) images for human recognition is proposed. Edge histogram based on edge intensity and its direction, has been used to detect effectively faces on NIR image. The edge histogram descripts and discriminates face effectively because it is strong in environment of lighting change. SVM(Support Vector Machine) has been used as a classifier to detect face and the proposed method showed better performance with smaller features than in ULBP(Uniform Local Binary Pattern) based method.

Edge Detection Using a Water Flow Model (Water Flow Model을 이용한 에지 검출)

  • Lee, Geon Il;Kim, In Gwon;Gwak, Won Gi;Park, Rae Hong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.98-98
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    • 2001
  • 본 논문에서는 영상의 그래디언트 (gradient)를 구하여 그래디언트 값의 분포를 마치 3차원 지형과 같은 개념으로 간주하고 여기에 물이 흐르는 개념을 적용한 에지 (edge) 검출 방법을 제안하였다 영상에서 그래디언트 값이 큰 부분은 배경과 객체간의 에지라 볼 수 있으며, 이 에지에 물이 고이게 하기 위해서는 반전된 그래디언트 영상을 사용한다. 반전된 그래디언트 영상에서 물의 흐름을 기반으로 한 enhancing 작업과 국부적응 임계값 적용을 실시하여 잡음을 줄인 에지 영상을 찾는 방법을 제안한다. 합성영상과 실제영상에 대한실험을 통해 제안한 방법의 효율성을 검증하였다.