• Title/Summary/Keyword: fuzzy edge detection

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Edge detection at subpixel accuracy using fuzzy logic (퍼지 논리를 이용한 Subpixel 정확도 Edge 검출)

  • 김영욱;양우석
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.105-108
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    • 1996
  • In this paper, we present an interpolation schema for image resolution enhancement using fuzzy logic. Proposed algorithm can recover both low and high frequency information in image data. In general, interpolation techniques are based on linear operators which are essentially details in the original image. In our fuzzy approach, the operator itself balances the strength of its sharpening and noise suppressing components according to the properties of the input image data. The proposed interpolation algorithm is performed in three step. First logic reasoning is applied to coarsely interpret the high frequency information. These results are combined to obtain the optical output. Using our approach, resolution of the original image can be applied to various kind of image processing topics such as image enhancement, subpixel edge detection, and filtering.

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Edge Detection By Fusion Using Local Information of Edges

  • Vlachos, Ioannis K.;Sergiadis, George D.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.403-406
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    • 2003
  • This paper presents a robust algorithm for edge detection based on fuzzy fusion, using a novel local edge information measure based on Renyi's a-order entropy. The calculation of the proposed measure is carried out using a parametric classification scheme based on local statistics. By suitably tuning its parameters, the local edge information measure is capable of extracting different types of edges, while exhibiting high immunity to noise. The notions of fuzzy measures and the Choquet fuzzy integral are applied to combine the different sources of information obtained using the local edge information measure with different sets of parameters. The effectiveness and the robustness of the new method are demonstrated by applying our algorithm to various synthetic computer-generated and real-world images.

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Automatic Edge Detection Method for Mobile Robot Application (이동로봇을 위한 영상의 자동 엣지 검출 방법)

  • Kim Dongsu;Kweon Inso;Lee Wangheon
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.5
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    • pp.423-428
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    • 2005
  • This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

Edge Detection in Blurred and Noisy Image Using Fuzzy Method (퍼지 기법을 이용한 열화된 영상에서의 에지 검출)

  • Jung, Jae-Woo;Chung, Tae-Yun;Jung, Jin-Yang;Huh, Jae-Man;Han, Young-Oh;Park, Sang-Hui
    • Proceedings of the KIEE Conference
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    • 1996.11a
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    • pp.294-296
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    • 1996
  • The process of detecting edge in an image is an important component of many Pattern Recognition and Computer Vision applications. In many practical cases, there exist blurred images due to defocussing, movement of an object and so on. In addition, local perturbation noise can be added to the images. We propose the edge detection technique in blurred and noisy image. For this, we use Fuzzy pyramid linking mothod to remove noise and enhance the edge in images. We develop contrast intensifier using the concept of Fuzzy sets as a postprocessing.

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COMPLETELY V-REGULAR ALGEBRA ON SEMIRING AND ITS APPLICATION IN EDGE DETECTION

  • G.E. CHATZARAKIS;S. DICKSON;S. PADMASEKARAN;J. RAVI
    • Journal of applied mathematics & informatics
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    • v.41 no.3
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    • pp.633-645
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    • 2023
  • In this paper, Completely V-Regular on semiring is defined and used to derive new theorems with some of its properties. This paper also illustrates V-Regular algebra and Completely V-Regular Algebra with examples and properties. By extending completely V-Regular to fuzzy, a new concept, fuzzy V-Regular is brought out and fuzzy completely V-Regular algebra is introduced too. It is also developed by defining the ideals of Completely V -Regular Algebra and fuzzy completely V-Regular algebra. Finally, this fuzzy algebra concept is applied in image processing to detect edges. This V-Regular Algebra is novel in the research area.

The Proposal of the Robust Fuzzy Wavelet Morphology Neural Networks Algorithm for Edge of Color Image (컬러 영상 에지에 강건한 퍼지 웨이브렛 형태학 신경망 알고리즘 제안)

  • Byun, Oh-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.53-62
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    • 2007
  • In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

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A Study on Canny Edge Detector Design Based on Image Fuzzification (이미지 퍼지화 기반 Canny 에지 검출기 설계에 관한 연구)

  • Park, Mi-Young;Kim, Chul-Won;Park, Jong-Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.9
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    • pp.1925-1931
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    • 2011
  • This paper suggests an approach to the subtle concept, "good", through the fuzzy logic and the design of the Canny edge detector of Gray scale images based on the rules of fuzzy anisotropic diffusion. The Canny edge detection algorithms design is to divide the gray levels into pixels and then calculate the diffusion coefficients at each pixel of non-edgy regions. Based on this processing, we present the Canny edge detector implementing fuzzy logic and comparing the results to other existing methods. The proposed approach is the narrow dynamic range of the gray-level image Sharpening the edge detection and has the advantage.

Evaluation of Edge Detector′s Smoothness using Fuzzy Ambiguity (퍼지 애매성을 이용한 에지검출기의 평활화 정도평가)

  • Kim, Tae-Yong;Han, Joon-Hee
    • Journal of KIISE:Software and Applications
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    • v.28 no.9
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    • pp.649-661
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    • 2001
  • While the conventional edge detection can be considered as the problem of determining the existence of edges at certain locations, the fuzzy edge modeling can be considered as the problem of determining the membership values of edges. Thus, if the location of an edge is unclear, or if the intensity function is different from the ideal edge model, the degree of edgeness at the location is represented as a fuzzy membership value. Using the concept of fuzzy edgeness, an automatic smoothing parameter evaluation and selection method for a conventional edge detector is proposed. This evaluation method uses the fuzzy edge modeling, and can analyze the effect of smoothing parameter to determine an optimal parameter for a given image. By using the selected parameter we can detect least ambiguous edges of a detection method for an image. The effectiveness of the parameter evaluation method is analyzed and demonstrated using a set of synthetic and real images.

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An Edge Detection for Face Feature Extraction using λ-Fuzzy Measure (λ-퍼지척도를 이용한 얼굴특징의 윤곽선 검출)

  • Park, In-Kue;Ahn, Bo-Hyeok;Choi, Gyoo-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.4
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    • pp.75-79
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    • 2009
  • In this paper the method was proposed which uses ${\lambda}$-fuzzy measure to detect the edge of the features of the face region. In the conventional method the features was founded using valley, brightness and edge. This method had its drawbacks that it is so sensitive to the external noises and environments. This paper proposed ${\lambda}$-fuzzy measure to cope with this drawbacks. By considering each weight of the pixels the integral evaluation was considered using the center of area method. Thus the continuity of the edge was kept by way of the neighborhood information and the reduction of time complexity wad resulted in.

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CFWC Scheme for Width Control using CCD Measurement System and Fuzzy PID Controller in Hot Strip Mills (CCD 폭 측정 시스템 및 퍼지 PID를 이용한 CFWC 제어기 설계)

  • Park, Cheol Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.991-997
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    • 2013
  • In this paper, we propose a CFWC (CCD and fuzzy PID based width control) scheme to obtain the desired delivery width margin of a vertical rolling mill in hot strip process. A WMS(width measurement system) is composed of two line scan cameras, an edge detection algorithm, a glitch filter, and so on. A dynamic model of the mill is derived from a gauge meter equation in order to design the fuzzy PID controller. The controller is a self-learning structure to select the PID gains from the error and error rate of the width margin. The effectiveness of the proposed CFWC is verified from simulation results under a width disturbance of the entry in the mill. Using a field test, we show that the performance of the width control is improved by the proposed control scheme.