• Title/Summary/Keyword: Edge function

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Estimating Directly Damage on External Surface of Container from Parameters of Capsize-Gaussian-Function

  • Son TRAN Ngoc Hoang;KIM Hwan-Seong
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2005.10a
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    • pp.297-302
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    • 2005
  • In this paper, an estimating damage on external surface of container using Capsize-Gaussian-Function (be called CGF) is presented. The estimation of the damage size can be get directly from two parameters of CGF, these are the depth and the flexure, also the direction of damage. The performance of the present method has been illustrated using an image of damage container, which had been taken from Hanjin Busan Port, after using image processing techniques to do preprocessing of the image, especially, the main used technique is Canny edge detecting that is widely used in computer vision to locate sharp intensity and to find object boundaries in the image, then correlation between the edge image from the preprocessing step and the CGF with three parameters (direction, depth, flexure), as a result, we get an image that perform damage information, and these parameters is an estimator directly to the damage.

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The Edge Distribution Function Based Method of Trajectory Tracking for AGV

  • Yi, Un-Kun;Ha, Sung-Kil;Jung, Sung-Yun;Hwang, Hee-Jung;Baek, Kwang-Ryul
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1701-1704
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    • 2005
  • We developed an machine vision method for navigation control of a traveling automatic guided vehicle(AGV) on desired trajectory with guided marks. The formulated EDF accumulates the edge magnitude for edge directions. The EDF has distinctive peak points at the vicinity of trajectory directions due to the directional and the positional continuities of desired trajectory. Examining the EDF by its shape parameters of the local maxima and symmetry axis results in identifying whether or not change in traveling direction of an AGV has occurred. Simulation results show that the presented method is useful for navigation control of AGV.

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Cost Maximization Approach to Edge Detection Using a Genetic Algorithm (유전자 알고리즘을 이용한 비용 최대화에 의한 에지추출)

  • 김수겸;박중순
    • Journal of Advanced Marine Engineering and Technology
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    • v.21 no.3
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    • pp.293-301
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    • 1997
  • Edge detection is the first step and very important step in image analysis. We cast edge detec¬tion as a problem in cost maximization. This is acheived by the formulation of a cost function that evaluates the quality of edge configurations. The cost function can be used as a basis for compar¬ing the performances of different detectors. We used a Genetic Algorithm for maximizing cost func¬tion. Genetic algorithms are a class of adaptive search techniques that have been intensively stud¬ied in recent years and have been prone to converge prematurely before the best solution has been found. This paper shows that carefully chosen modifications(three factors of the crossover opera¬tor) are implemented can be effective in alleviating this problem.

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Edge Detection of Characters on the Rubber Tire Image Using Fuzzy $\alpha-Cut$ Set (퍼지 $\alpha$ 컷 집합에 의한 고무 타이어 영상의 문자 윤관선 추출)

  • 김경민;박중조;박귀태
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.6
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    • pp.71-80
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    • 1994
  • The purpose of this paper is to explore the use of fuzzy set theory for image processing and analysis. As an application example, the fuzzy method of edge detection is proposed to extract the edges of raised characters on tires.In general, Sobel, Prewitt, Robert and LoG filters are used to detect the edge, but it is difficult to detect the edge because of ambiguity of representations, noise and general problems in the interpretation of tire image. Therefore, in his paper, the fuzzy property plane has been extracted from the spatial domain using the ramp-mapping function. And then the ideas of fuzzy MIN and MAX are applied in removing noise and enhancement of the image simultaneously. From the result of MIN and MAX procedure a new fuzzy singleton is generated by extracting the difference between adjacent membership function values. And the edges are extracted by applying fuzzy $\alpha$-cut set to the fuzzy singletion, Finally, these ideas are applied to the tire images.

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Modified energy function of the active contour model for the tracking of deformable objects

  • Choi, Jeong, Ju;Kim, Jong-Shik
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.1
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    • pp.47-50
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    • 2006
  • An active contour model has been used to detect the edges in a still image. In order to apply the active contour model to edge detection, the energy function which consists of internal, external and image energies should be defined. After defining the energy function, the edge of an object is detected through minimization of the value of the energy function. In this paper, the modified internal energy function is proposed to improve the convergence of the energy function when the active contour model is applied to the tracking of deformable objects using the greedy algorithm. In order to show the performance of the proposed energy function, experiments were carried out for the still and animated images.

Edge-Preserving Iterative Reconstruction in Transmission Tomography Using Space-Variant Smoothing (투과 단층촬영에서 공간가변 평활화를 사용한 경계보존 반복연산 재구성)

  • Jung, Ji Eun;Ren, Xue;Lee, Soo-Jin
    • Journal of Biomedical Engineering Research
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    • v.38 no.5
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    • pp.219-226
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    • 2017
  • Penalized-likelihood (PL) reconstruction methods for transmission tomography are known to provide improved image quality for reduced dose level by efficiently smoothing out noise while preserving edges. Unfortunately, however, most of the edge-preserving penalty functions used in conventional PL methods contain at least one free parameter which controls the shape of a non-quadratic penalty function to adjust the sensitivity of edge preservation. In this work, to avoid difficulties in finding a proper value of the free parameter involved in a non-quadratic penalty function, we propose a new adaptive method of space-variant smoothing with a simple quadratic penalty function. In this method, the smoothing parameter is adaptively selected for each pixel location at each iteration by using the image roughness measured by a pixel-wise standard deviation image calculated from the previous iteration. The experimental results demonstrate that our new method not only preserves edges, but also suppresses noise well in monotonic regions without requiring additional processes to select free parameters that may otherwise be included in a non-quadratic penalty function.

An MPLS VPN with Mobility Support (이동성을 지원하는 MPLS 방식 가상사설망)

  • Lee, Young-Seok;Choi, Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.12C
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    • pp.225-232
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    • 2001
  • In this paper, we describe a mechanism that supports the mobility service for VPN(Virtual Private Network) users on MPLS(Multiprotocol Label Switching) network. The MPLS VPN considered in this study is controlled by CE(Customer Edge) routers. In such a VPN, CE routers have additional functions to support mobile VPN users, i.e., Home Agent function, foreign Agent function, Correspondent Agent function. This mechanism is applied when a VPN node moves to other site of the saute VPN, or when it moves to other site of a different VPN, or to a non-VPN site. We perform a simulation study to compare the performance of CE based MPLS VPN with that of PE(Provider Edge) based MPLS VPN with mobility support.

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Road-Lane Detection Based on a Cumulative Distribution Function of Edge Direction

  • Yi, Un-Kun;Lee, Joon-Woong;Baek, Kwang-Ryul
    • Journal of KIEE
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    • v.11 no.1
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    • pp.69-77
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    • 2001
  • This paper describes an image processing algorithm capable of recognizing road lanes by using a CDF(cumulative distribution function). The CDF is designed for the model function of road lanes. Based on the assumptions that there are no abrupt changes in the direction and location of road lanes and that the intensity of lane boundaries differs from that of the background, we formulated the CDF, which accumulates the edge magnitude for edge directions. The CDF has distinctive peak points at the vicinity of lane directions due to the directional and the positional continuities of a lane. To obtain lane-related information a scatter diagram was constructed by collecting edge pixels, of which the direction corresponds to the peak point of the CDF, then the principal axis-based line fitting was performed for the scatter diagram. Noises can cause many similar features to appear and to disappear in an image. Therefore, to reduce the noise effect a recursive estimator of the CDF was introduced, and also to prevent false alarms or miss detection a scene understanding index (DUI) was formulated by the statistical parameters of the CDF. The proposed algorithm has been implemented in real time on video data obtained from a test vehicle driven on a typical highway.

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Edge Enhanced Error Diffusion based on Local Average of Original Image (원영상의 로컬 평균을 이용한 경계강조 오차확산법)

  • Kang, Tae-Ha;Hwang, Byong-Won
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.8
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    • pp.2565-2574
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    • 2000
  • The error diffusion method is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysis of display error. In this paper. we present an edge-enhanced error-diffusion method which include pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm consists of the difference value between current pixel and local average of original image and weighting function of pre-filter. First. it is obtained the difference value between current pixel and the local average of peripheral pixels(5x5) in original image. Second, weighting function of pre-filter is composed by function including absolute value and sign of difference value. The improved Error diffusion algorithm using pre-processing algorithm, present a good result visually which edge characteristic is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

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A Study on Improving Data Poisoning Attack Detection against Network Data Analytics Function in 5G Mobile Edge Computing (5G 모바일 에지 컴퓨팅에서 빅데이터 분석 기능에 대한 데이터 오염 공격 탐지 성능 향상을 위한 연구)

  • Ji-won Ock;Hyeon No;Yeon-sup Lim;Seong-min Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.549-559
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    • 2023
  • As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.