• Title/Summary/Keyword: edge-detection algorithm

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A Study on Edge Detection using Weighted Value with Threshold (임계값에 따른 가중치를 이용한 에지 검출에 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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    • 2013.05a
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    • pp.886-888
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    • 2013
  • An edge includes information of objects such as magnitude, orientation, and location. Conventional edge detection methods to detect those edge are methods using Sobel, Prewitt, Roberts, Laplacian operator. Existing methods use fixed weighted mask to detect edges, and their edge detection characteristics are insufficient. Therefore, to remedy weakness of conventional methods, in this paper, an edge detection algorithm using weight with standard deviation and thresholds is proposed.

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A Study on the Edge Detection using Region Segmentation of the Mask (마스크의 영역 분할을 이용한 에지 검출에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.718-723
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    • 2013
  • In general, the boundary portion of the background and objects are the rapidly changing point and an important elements to analyze characteristics of image. Using these boundary parts, information about the position or shape of an object in the image are detected, and many studies have been continued in order to detect it. Existing methods are that implementation of algorithm is comparatively simple and its processing speed is fast, but edge detection characteristics is insufficient because weighted values are applied to all the pixels equally. Therefore, in this paper, we proposed an algorithm using region segmentation of the mask in order to adaptive edge detection according to image, and the results processed by proposed algorithm indicated superior edge detection characteristics in edge area.

Edge Detection Method using Modified Coefficient Masks (변형된 계수 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Chung, Suk-Moon;Kim, Nam-Ho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.218-223
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    • 2013
  • The performances of previous edge detection methods such as Sobel, Prewitt, and LoG(Laplacian of Gaussian) are insufficient for images degraded in AWGN(additive white Gaussian noise). Therefore, in this paper, we proposed an edge detection algorithm using a modified coefficient masks with gradient masks and distance weight mask. In order to confirm and verify the performance of the proposed algorithm, we simulated and compared proposed algorithm to conventional methods on various standard images added AWGN with a standard deviation ${\sigma}$=15, 30 and proposed algorithm shows superior edge detection characteristics in processed images.

Edge Detection of Ultrasonic Image Using Neighhood Mean Intensity Difference (주변 평균 밝기차를 이용한 초음파 영상의 에지 검출)

  • Won, Chul-Ho;Koo, Sung-Mo;Kim, Myoung-Nam;Cho, Jin-Ho
    • Proceedings of the KOSOMBE Conference
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    • v.1994 no.05
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    • pp.23-26
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    • 1994
  • A new algorithm using a measure for edge detection from ultrasonic image is proposed. Ultrasonic image is blurred by pre-processing for removing speckle noises and precise edge placement is not clear. Because extracted edge from blurred image is thick, a measure utilizing the absolute difference of mean between two windows is used to thin the thickness of extracted edge in blurred image. The algorithm is effective to process blurred image due to the noise filtering that remove speckle noises. Results of the proposed algorithm using a measure show good edge detection performance comparing with other gradient edge operators.

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CMOS Clockless Wave Pipelined Adder Using Edge-Sensing Completion Detection (에지완료 검출을 이용한 클럭이 없는 CMOS 웨이브파이프라인 덧셈기 설계)

  • Ahn, Yong-Sung;Kang, Jin-Ku
    • Journal of IKEEE
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    • v.8 no.2 s.15
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    • pp.161-165
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    • 2004
  • In this paper, an 8bit wave pipelined adder using the static CMOS plus Edge-Sensing Completion Detection Logic is presented. The clockless wave-pipelining algorithm was implemented in the circuit design. The Edge-Sensing Completion Detection (ESCD) in the algorithm is consisted of edge-sensing circuits and latches. Using the algorithm, skewed data at the output of 8bit adder could be aligned. Simulation results show that the adder operates at 1GHz in $0.35{\mu}m$ CMOS technology with 3.3V supply voltage.

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A Measurement of Heart Ejection Fraction using Automatic Detection of Left Ventricular Boundary in Digital Angiocardiogram (디지탈 혈관 조영상에서의 좌심실 경계 자동검출을 이용한 심박출 계수의 측정)

  • 구본호;이태수
    • Journal of Biomedical Engineering Research
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    • v.8 no.2
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    • pp.177-188
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    • 1987
  • Detection of left ventricular boundary for the functional analysis of LV(left ventricle) is obtained using automatic boundary detection algorithm based on dynamic program ming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge detection methods. The left ventricular diastolic volume and systolic volume were computed after this automatic boundary detection, and these volume data were applied to analyze LV ejection fraction.

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Edge Detection Using Simulated Annealing Algorithm (Simulated Annealing 알고리즘을 이용한 에지추출)

  • Park, J.S.;Kim, S.G.
    • Journal of Power System Engineering
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    • v.2 no.3
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    • pp.60-67
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    • 1998
  • Edge detection is the first step and very important step in image analysis. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that evaluates the quality of edge configurations. The cost function can be used as a basis for comparing the performances of different detectors. This cost function is made of desirable characteristics of edges such as thickness, continuity, length, region dissimilarity. And we use a simulated annealing algorithm for minimum of cost function. Simulated annealing are a class of adaptive search techniques that have been intensively studied in recent years. We present five strategies for generating candidate states. Experimental results(building image and test image) which verify the usefulness of our simulated annealing approach to edge detection are better than other operator.

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Gradual Scene Change Detection Using Variance of Edge Image (에지 영상의 분산을 이용한 비디오의 점진적 장면전환 검출)

  • Ryoo, Han-Jin;Yoo, Hun-Woo;Jang, Dong-Sik;Kim, Mun-Hwa
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.3
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    • pp.275-280
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    • 2002
  • A new algorithm for gradual scene change detection in MPEG based frame sequences is proposed in this paper. The proposed algorithm is based on the fact that most of gradual curves can be characterized by variance distributions of edge information in the frame sequences. Average edge frame sequences are obtained by performing "sober" edge detection. Features are extracted by comparing variances with those of local blocks in the average edge frames. Those features are further processed by the opening operation to obtain smoothing variance curves. The lowest variance in the local frame sequences is chosen as a gradual detection point. Experimental results show that the proposed method provides 85% precision and 86% recall rate fur gradual scene changes.

A Study on Edge Detection Algorithm using Mask Shifting Deviation (마스크 이동 편차를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • 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.

A Method for Quantitative Performance Evaluation of Edge Detection Algorithms Depending on Chosen Parameters that Influence the Performance of Edge Detection (경계선 검출 성능에 영향을 주는 변수 변화에 따른 경계선 검출 알고리듬 성능의 정량적인 평가 방법)

  • 양희성;김유호;한정현;이은석;이준호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.993-1001
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    • 2000
  • This research features a method that quantitatively evaluates the performance of edge detection algorithms. Contrary to conventional methods that evaluate the performance of edge detection as a function of the amount of noise added to he input image, the proposed method is capable of assessing the performance of edge detection algorithms based on chosen parameters that influence the performance of edge detection. We have proposed a quantitative measure, called average performance index, that compares the average performance of different edge detection algorithms. We have applied the method to the commonly used edge detectors, Sobel, LOG(Laplacian of Gaussian), and Canny edge detectors for noisy images that contain straight line edges and curved line edges. Two kinds of noises i.e, Gaussian and impulse noises, are used. Experimental results show that our method of quantitatively evaluating the performance of edge detection algorithms can facilitate the selection of the optimal dge detection algorithm for a given task.

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