• Title/Summary/Keyword: Edge Detection

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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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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.

Triqubit-State Measurement-Based Image Edge Detection Algorithm

  • Wang, Zhonghua;Huang, Faliang
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1331-1346
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    • 2018
  • Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

A Study on Edge Detection Algorithm using Modified Directional Masks (변형된 방향성 마스크를 이용한 에지검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.244-246
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    • 2014
  • Edge detection is a technique that obtains the particular information of the image using the brightness variation of pixel values and utilized for preprocessing in various image processing sectors. The conventional edge detection methods such as Sobel, Prewitt and Roberts are processed by applying the same weighted value to the entire pixels regardless of pixel distribution and provides somewhat insufficient edge detection results. Therefore, this paper has proposed an edge detection algorithm considering the direction and size of pixels by applying a modified directional mask.

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Fuzzy Classifier System for Edge Detection

  • Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.52-57
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    • 2003
  • In this paper, we propose a Fuzzy Classifier System(FCS) to find a set of fuzzy rules which can carry out the edge detection. The classifier system of Holland can evaluate the usefulness of rules represented by classifiers with repeated learning. FCS makes the classifier system be able to carry out the mapping from continuous inputs to outputs. It is the FCS that applies the method of machine learning to the concept of fuzzy logic. It is that the antecedent and consequent of classifier is same as a fuzzy rule. In this paper, the FCS is the Michigan style. A single fuzzy if-then rule is coded as an individual. The average gray levels which each group of neighbor pixels has are represented into fuzzy set. Then a pixel is decided whether it is edge pixel or not using fuzzy if-then rules. Depending on the average of gray levels, a number of fuzzy rules can be activated, and each rules makes the output. These outputs are aggregated and defuzzified to take new gray value of the pixel. To evaluate this edge detection, we will compare the new gray level of a pixel with gray level obtained by the other edge detection method such as Sobel edge detection. This comparison provides a reinforcement signal for FCS which is reinforcement learning. Also the FCS employs the Genetic Algorithms to make new rules and modify rules when performance of the system needs to be improved.

A Study for Image Segmentation Using Java (Java를 이용한 영상분할에 관한 연구)

  • 신민화;최길환;배상현
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.804-807
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    • 2002
  • Edge of image have a many information about input image. There is a many applications to using a edge detection and uses by variable special effect. Edge detection is a field of image analysis, image segmentation using a pixel make the one field for decision of image construction. In this paper, image segmentation through many ways of edge detection for image segmentation. First of all, it analyze feature of image and extract by feature of each image, to adopt way of edge detection to selective. It realize edge detection efficiently, consider to feature of language through using a java image segmentation.

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An Edge Detection Method using Modified Mask in Impulse Noise and AWGN Environments (임펄스 잡음 및 AWGN 환경에서 변형된 마스크를 이용한 에지 검출 방법)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.265-267
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    • 2013
  • Edges include various important informations of the objects. These edges are being applied in numerous areas and there is a detection method using mask in existing edge detection methods. These existing edge detection methods are simple to realize. However, because the fixed mask is used, edge detection characteristics in complicated noise environments are somewhat unsatisfactory. Therefore, to compensate for the weakness in the existing detection methods, edge detection algorithm which uses the standard deviation of local mask and noise elimination was proposed.

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A Study on Edge Detection Method using Modified Directional Masks (변형된 방향성 마스크를 이용한 에지검출 방법에 관한 연구)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2779-2785
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    • 2014
  • Edge Detection is a technique that obtains the particular information of the image using the brightness variation of pixel values and utilized for preprocessing in various image processing sectors. The conventional edge detection methods such as Sobel, Prewitt and Roberts are processed by applying the same weighted value to the entire pixels regardless of pixel distrbution and provides somewhat insufficient edge detection results. therefore, this paper has proposed an edge detection method considering the direction and magnitute of pixels by applying a modified directional mask.

A Study on Edge Detection using Pixel Brightness Transfer Function in Low Light Level Environments (저조도 환경에서 화소의 휘도 변환 함수를 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.19 no.7
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    • pp.1680-1686
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    • 2015
  • Edge detection is an essential preprocessing for most image processing application, and there are several existing detection methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) operators, etc. Those existing edge detection methods have not given satisfactory results since they do not offer enough pixel brightness change in low light level environment. Therefore, in this study new algorithms using brightness transfer function in the preprocessing and for edge detection applying standard deviation and average-weighted local masks are proposed. In addition, the performance of proposed algorithms was evaluated in comparison with the existing edge detection methods such as Sobel, Roberts, Prewitt, Laplacian, LoG operators.

A light-adaptive CMOS vision chip for edge detection using saturating resistive network (포화 저항망을 이용한 광적응 윤곽 검출용 시각칩)

  • Kong, Jae-Sung;Suh, Sung-Ho;Kim, Jung-Hwan;Shin, Jang-Kyoo;Lee, Min-Ho
    • Journal of Sensor Science and Technology
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    • v.14 no.6
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    • pp.430-437
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    • 2005
  • In this paper, we proposed a biologically inspired light-adaptive edge detection circuit based on the human retina. A saturating resistive network was suggested for light adaptation and simulated by using HSPICE. The light adaptation mechanism of the edge detection circuit was quantitatively analyzed by using a simple model of the saturating resistive element. A light-adaptive capability of the edge detection circuit was confirmed by using the one-dimensional array of the 128 pixels with various levels of input light intensity. Experimental data of the saturating resistive element was compared with the simulated results. The entire capability of the edge detection circuit, implemented with the saturating resistive network, was investigated through the two-dimensional array of the $64{\times}64$ pixels