• Title, Summary, Keyword: edge detection

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Kidney's feature point extraction based on edge detection using SIFT algorithm in ultrasound image (Edge detection 기반의 SIFT 알고리즘을 이용한 kidney 특징점 검출 방법)

  • Kim, Sung-Jung;Yoo, JaeChern
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.89-90
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    • 2019
  • 본 논문에서는 ultrasound image Right Parasagittal Liver에 edge detection을 적용한 후, 특징점 검출 알고리즘인 Scale Invarient Feature Transfom(SIFT)를 이용하여 특징점의 위치를 살펴보도록 한다. edge detection 알고리즘으로는 Canny edge detection과 Prewitt edge detection을 적용하기로 한다.

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The Generation of a TM Mask Using the AM Technique and the Edge Detection Algorithm for a SAR Image (AM 기법을 이용한 TM 마스크의 형성 및 SAR 영상의 경계검출 알고리듬)

  • 한수용;최성진;라극환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.4
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    • pp.36-47
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    • 1992
  • In this paper, a set of TM(template matching) mask using the AM(associative mapping) technique was generated and the edge detection algorithm for a SAR image was proposed. And also, the performance of the proposed edge detection algorithm was tested with the conventional edge detection techniques. The proposed edge detection algorithm created an edge image which was more accurate and clear than the conventional edge detection techniques and the performance of the proposed detection technique was not deteriorated for low intensity area in the image because the uncertainly thresholded value genetated by the conventional detection methods was requested. Also, the number of masks and the detection time were reduced by adjusting resolution of edge detection and the consideration for the threshold value extracting the edge was very intuitive.

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Edge Detection Using the Information of Edge Structural Regions (에지의 구조적 영역정보를 이용한 에지검출)

  • 김수겸;박중순;최정희
    • Journal of the Korean Society of Marine Engineering
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    • v.24 no.2
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    • pp.82-89
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    • 2000
  • Edge detection is the first step and very important step in image analysis. In this paper, proposed edge detection operators based on informations of edge types and it is different from other classical edge detection operators such as gradient and surface fitting operators. The first, we defined characteristics of edge types such as localization, thinness, length. The second, we defined valid edge types and ideal edge pixel positions in $3\times3$window based on edge characteristics of edge types. And we proposed edge detection algorithm and twelve windows based on valid edge types. In specially, proposed algorithm was shown better performence of edge detection than other operators such as gradient operator and the LoG(Laplacian of Gaussian) operator of zero crossings.

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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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Development of an Edge-Based Algorithm for Moving-Object Detection Using Background Modeling

  • Shin, Won-Yong;Kabir, M. Humayun;Hoque, M. Robiul;Yang, Sung-Hyun
    • Journal of information and communication convergence engineering
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    • v.12 no.3
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    • pp.193-197
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    • 2014
  • Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of the ultimate moving edges, a temporary background-edge map was created. If the frequencies of the temporary background edge pixels for several frames were above the threshold, then those edge pixels were treated as background edge pixels. We conducted a performance comparison with previous works. The existing edge-based moving-object detection algorithms pose some difficulty due to the changes in background motion, object shape, illumination variation, and noises. The result of the performance evaluation shows that the proposed algorithm can detect moving objects efficiently in real-world scenarios.

A Study on Edge Detection Algorithm using Standard Deviation of Local Mask (국부 마스크의 표준편차를 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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    • pp.328-330
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    • 2015
  • Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

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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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Detection of Edges in Color Images

  • Ganchimeg, Ganbold;Turbat, Renchin
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.6
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    • pp.345-352
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    • 2014
  • Edge detection considers the important technical details of digital image processing. Many edge detection operators already perform edge detection in digital color imaging. In this study, the edge of many real color images that represent the type of digital image was detected using a new operator in the least square approximation method, which is a type of numerical method. The Linear Fitting algorithm is computationally more expensive compared to the Canny, LoG, Sobel, Prewitt, HIS, Fuzzy, Parametric, Synthetic and Vector methods, and Robert' operators. The results showed that the new method can detect an edge in a digital color image with high efficiency compared to standard methods used for edge detection. In addition, the suggested operator is very useful for detecting the edge in a digital color image.

Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.2 no.1
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

Real time image processing and measurement of heart parameter using digital subtraction angiography (디지탈 혈관 조영장치를 이용한 실시간 영상처리와 심장파라미터의 측정)

  • 신동익;구본호;박광석;민병구;한만청
    • 제어로봇시스템학회:학술대회논문집
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    • pp.570-574
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    • 1990
  • Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming 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 and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

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