• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1329-1336
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• 2005

We propose an optimal edge detection algorithm adaptive to the various widths of edges. In order to construct this algorithm, we introduce an alternative definition of edge point and generalize the directional derivatives in the pixel space to obtain an extended directional derivatives beyond scaling. The result from applying our algorithm to a 2D image is analyzed comparing to that from the other algorithm.

• Journal of the Korea Computer Industry Society
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• v.3 no.12
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• pp.1725-1736
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• 2002

We describe a characteristic behavior of edge signal intensity, the strictly monotonic variation of intensity across edges and propose a new algorithm for edge detection based on it. We define an extended directional derivatives, which is nonlocal and beyond scaling in the pixel space, to describe that the algorithm is adaptive to the various widths of edges and relevant as an optimal edge detection algorithm. As an industrial application of the algorithm, we discuss a simple computer vision procedure for an example of visual inspection.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.663-670
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• 2019

The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.241-248
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• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.901-908
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• 2016

Edge is the basic characteristic of image, edge detection is very important in image processing applications and computer vision area. Many studies are being performed to detect these edges by domestic and foreign researchers. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask are widely used and morphological gradient which uses dilation and erosion among morphology process techniques is also widely used. But these methods does not detect edges well in the diagonal direction or gradually changing image parts. Accordingly, in this paper, the modified top-hat and bottom-hat transform algorithms which are detecting edges well in the parts of diagonal direction or gradually changing image are proposed. The proposed algorithms present the detected edge images compared with the conventional methods and are evaluated performance by using cosine similarity.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.385-388
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• 2001

본 논문에서는 비디오 영상에서 장면 전환을 검출하는 알고리듬을 제안한다. 장면 전환 검출은 비디오 프레임 사이의 유사도를 측정하여 이루어 진다. 유사도는 비디오 영상의 특성을 나타내는 지표를 추출하고 이를 비교함으로써 얻어진다. 비디오 영상의 특성 지표는 비디오 영상 전체에서 추출하는 것이 일반적이나 제안하는 알고리듬에서는 비디오 영상에서 강한 에지 부분을 포함하는 여러개의 블록에서만 추출된다. 이렇게 함으로써 배경보다 더 중요한 정보를 가진 에지 주변의 칼라 변화에 집중하는 효과를 얻게된다. 실험 결과는 강한 에지 블록에서 얻은 지표가 점진적 장면 전환(dissolve, wipe) 검출에 효과적임을 보여준다. 제안하는 알고리듬은 또한 Cut탐지에도 비교적 좋은 성능을 보인다. 그리고 Fade-in/out을 간단하면서 효과적으로 탐지할 수 있는 방법을 제시한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.130-133
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• 2014

본 논문은 Laplacian of Gaussians (LoG)에 캐니 에지 검출 기법을 접목한 새로운 색상 보간 알고리듬을 제안한다. 캐니 에지 검출 기법은 영상 스무딩, 기울기 크기와 각도 계산, 세션화, 이중 문턱치 처리 과정으로 이루어진다. 이때 앞의 두 과정을 LoG를 이용하여 처리함으로써 기존의 캐니 애지 검출법보다 정확한 방향 정보를 얻을 수 있다. 실험결과를 통해 기존의 색상 보간 알고리듬에 비해 Peak Signal to Noise Ratio (CPSNR)이 상승함을 확인하였으며, 에지 영역 주변에서 발생하였던 무지개 에러가 현저히 감소하였음을 확인할 수 있었다.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1051-1058
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• 2018

This paper propose image processing algorithm to prevent safety accidents near by subway platform screen door(PSD). First, edges of the subway PSD images are detected and the boundary line between PSD and subway platform is detected to decide people's approach to the PSD using Hough transform. To do this, we draw the boundary line between the PSD and platform, to detect the boundary line and to decide the people's approach to the detected line is completely connected or not. Generally, edge is the basic characteristic of image; thus, edge detection is very important in image processing applications and computer vision area. The conventional edge detection methods such as Roberts, Sobel, Prewitt, and Laplacian etc, which are using a fixed value of mask, and morphological gradient from the structuring element of view and Canny edge detector are widely used. In this paper, we propose the detection algorithm about the people's approach to the subway PSD to prevent the safety accidents by using Canny edge detector and Hough transform and the computer simulation shows the results.

• Convergence Security Journal
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• v.7 no.3
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• pp.39-44
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• 2007

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Convergence Security Journal
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• v.6 no.3
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• pp.29-35
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• 2006

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.