• Title/Summary/Keyword: Edge detection

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A Study on Edge Detection Considering Center Pixels of Mask (마스크의 중심 화소를 고려한 에지 검출에 관한 연구)

  • Park, Hwa-Jung;Jung, Hwae-Sung;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.136-138
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    • 2022
  • Edge detection includes information such as the shape, position, size, and material of an object with respect to an image, and is a very important factor in analyzing the characteristics of the image. Existing edge detection methods include Sobel edge detection filter, Roberts edge detection filter, Prewitt edge detection filter, and LoG (Lapacian of Gaussian) using secondary differentials. However, these methods have a disadvantage in that the edge detection results are somewhat insufficient because a fixed weight mask is applied to the entire image area. Therefore, in this paper, we propose an edge detection algorithm that increases edge detection characteristics by considering the center pixel in the mask. In addition, in order to confirm the proposed edge detection performance, it was compared through simulation result images.

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Edge Detection based on Contrast Analysis in Low Light Level Environment (저조도 환경에서 명암도 분석 기반의 에지 검출)

  • Park, Hwa-Jung;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.437-440
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    • 2022
  • In modern society, the use of the image processing field is increasing rapidly due to the 4th industrial revolution and the development of IoT technology. In particular, edge detection is widely used in various fields as an essential preprocessing process in image processing applications such as image classification and object detection. Conventional methods for detecting an edge include a Sobel edge detection filter, a Roberts edge detection filter, a Prewitt edge detection filter, Laplacian of Gaussian (LoG), and the like. However, existing methods have the disadvantage of showing somewhat insufficient performance of edge detection characteristics in a low-light level environment with low contrast. Therefore, this paper proposes an edge detection algorithm based on contrast analysis to increase edge detection characteristics even in low-light level environments.

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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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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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    • 2019.07a
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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 Advanced Marine Engineering and Technology
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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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Edge detection for noisy image (잡음 영상에서의 에지 검출)

  • Koo, Yun Mo;Kim, Young Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.3
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    • pp.41-48
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    • 2012
  • In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

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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    • 2015.10a
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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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