• Title/Summary/Keyword: fuzzy edge detection

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A Motion Detection Approach based on UAV Image Sequence

  • Cui, Hong-Xia;Wang, Ya-Qi;Zhang, FangFei;Li, TingTing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1224-1242
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    • 2018
  • Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

A New Fuzzy Supervised Learning Algorithm

  • Kim, Kwang-Baek;Yuk, Chang-Keun;Cha, Eui-Young
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.399-403
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    • 1998
  • In this paper, we proposed a new fuzzy supervised learning algorithm. We construct, and train, a new type fuzzy neural net to model the linear activation function. Properties of our fuzzy neural net include : (1) a proposed linear activation function ; and (2) a modified delta rule for learning algorithm. We applied this proposed learning algorithm to exclusive OR,3 bit parity using benchmark in neural network and pattern recognition problems, a kind of image recognition.

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Fuzzy Navigation Control of Mobile Robot equipped with CCD Camera (퍼지제어를 이용한 카메라가 장착된 이동로봇의 경로제어)

  • Cho, Jung-Tae;Lee, Seok-Won;Nam, Boo-Hee
    • Journal of Industrial Technology
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    • v.20 no.B
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    • pp.195-200
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    • 2000
  • This paper describes the path planning method in an unknown environment for an autonomous mobile robot equipped with CCD(Charge-Coupled Device) camera. The mobile robot moves along the guideline. The CCD camera is used for the detection of the existence of a guideline. The wavelet transform is used to find the edge of guideline. It is possible for us to do image processing more easily and rapidly by using wavelet transform. We make a fuzzy control rule using image data as an input then determined the position and the navigation of the mobile robot. The center value of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy controller output. Some actual experiments show that the mobile robot effectively moves to target position by means of the applied fuzzy control.

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Edge Detection in noisy Images by means of Fuzzy Entropy (퍼지엔트로피에 의한 잡음영상의 경계검출)

  • 박인규
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.04a
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    • pp.170-173
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    • 2000
  • 잡음에 오염된 영상의 경계검출에 대한 퍼지연산자를 보강하였다. 제한된 방법은 데이터에 존재하는 잡음에 강인한 경계를 검출하기 위하여 퍼지 엔트로피에 의한 퍼지추론을 이용한다. 퍼지기법이 영상의 세세한 정보의 검출과 잡음에 대한 민감도의 관점에서 보았을 때 기존의 방법들보다 성능이 우수하다는 것을 여러 실험결과를 통하여 알 수 있었다.

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Using Mean Shift Algorithm and Self-adaptive Canny Algorithm for I mprovement of Edge Detection (경계선 검출의 향상을 위한 Mean Shift 알고리즘과 자기 적응적 Canny 알고리즘의 활용)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.7
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    • pp.33-40
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    • 2009
  • Edge detection is very significant in low level image processing. However, majority edge detection methods are not only effective enough cause of the noise points' influence, even not flexible enough to different input images. In order to sort these problems, in this paper an algorithm is presented that has an extra noise reduction stage at first, and then automatically selects the both thresholds depending on gradient amplitude histogram and intra class minimum variance. Using this algorithm, can fade out almost all of the sensitive noise points, and calculate the propose thresholds for different images without setting up the practical parameters artificially, and then choose edge pixels by fuzzy algorithm. In finally, get the better result than the former Canny algorithm.

A Study on 3Dimensional Automatic Boundaries Detection on Medical Images or Radiation Therapy Planning (방사선 치료 계획 장치를 위한 의료 영상의 3차원적 자동 경계선 검출에 관한 연구)

  • Choi, Eun-Jin;Suh, Doug-Young
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.11
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    • pp.172-175
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    • 1997
  • Outline contour is detected firstly to simulate dose distribution in radiation therapy planning system. In this paper, we developed automatic contour detection system using temporal and spatial relationships of image sequences. The low level image analysis involves the use of directional gradient edge operators and Laplacian operator. The High level portion of algorithm uses a knowledge-based strategy that incorporates fuzzy resoning method.

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A Possibilistic C-Means Approach to the Hough Transform for Line Detection

  • Frank Chung-HoonRhee;Shim, Eun-A
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.476-479
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    • 2003
  • The Rough transform (HT) is often used for extracting global features in binary images, for example curve and line segments, from local features such as single pixels. The HT is useful due to its insensitivity to missing edge points and occlusions, and robustness in noisy images. However, it possesses some disadvantages, such as time and memory consumption due to the number of input data and the selection of an optimal and efficient resolution of the accumulator space can be difficult. Another problem of the HT is in the difficulty of peak detection due to the discrete nature of the image space and the round off in estimation. In order to resolve the problem mentioned above, a possibilistic C-means approach to clustering [1] is used to cluster neighboring peaks. Several experimental results are given.

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A Edge Detection Method using The Fuzzy Function in Satellite Remote Sensing Image (위성탐사 영상에서 퍼지함수를 이용한 윤곽선 추출기법)

  • 전영준;김진일
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.04a
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    • pp.178-183
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    • 2000
  • 본 연구는 위성탐사 이미지에서 탑재 센서가 갖는 한계인 공간해상도의 문제를 퍼지함수의 정의를 이용하여 해석하는 방법을 제안한다. 이는 한 화소(SPOT 의 HRV의 경우 20 m$\times$20m)에 포함된 혼합정보들의 내용을 예측할 수 있으며, 대비되는 화소 군집들간에서의 윤곽선 추출이 가능해진다. 본 연구의 결과는 Landsat TM 위성이미지에서 강 유역의 경계선과 교량의 중앙선 추출에 적용시켜 보았으며 ,만족할 만한 결과를 보였다.

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Caricaturing using Local Warping and Edge Detection (로컬 와핑 및 윤곽선 추출을 이용한 캐리커처 제작)

  • Choi, Sung-Jin;Bae, Hyeon;Kim, Sung-Shin;Woo, Kwang-Bang
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.403-408
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    • 2003
  • A general meaning of caricaturing is that a representation, especially pictorial or literary, in which the subject's distinctive features or peculiarities are deliberately exaggerated to produce a comic or grotesque effect. In other words, a caricature is defined as a rough sketch(dessin) which is made by detecting features from human face and exaggerating or warping those. There have been developed many methods which can make a caricature image from human face using computer. In this paper, we propose a new caricaturing system. The system uses a real-time image or supplied image as an input image and deals with it on four processing steps and then creates a caricatured image finally. The four Processing steps are like that. The first step is detecting a face from input image. The second step is extracting special coordinate values as facial geometric information. The third step is deforming the face image using local warping method and the coordinate values acquired in the second step. In fourth step, the system transforms the deformed image into the better improved edge image using a fuzzy Sobel method and then creates a caricatured image finally. In this paper , we can realize a caricaturing system which is simpler than any other exiting systems in ways that create a caricatured image and does not need complex algorithms using many image processing methods like image recognition, transformation and edge detection.

Caricaturing using Local Warping and Edge Detection (로컬 와핑 및 윤곽선 추출을 이용한 캐리커처 제작)

  • Choi, Sung-Jin;Kim, Sung-Sin;Bae, Hyun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.05a
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    • pp.137-140
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    • 2003
  • 캐리커처의 일반적인 의미는 어떤 사람이나 사물의 특징을 추출하여 익살스럽게 풍자한 그림이나 글이다. 다시 말해, 캐리커처는 사람의 얼굴에서 특징을 잡아 과장하거나 왜곡하여 그린 데생이라고 한다. 컴퓨터를 이용한 기존의 캐리커처 제작방법으로는, 입력 이미지 좌표의 통계적인 차이값을 이용하는 PICASSO System 방법[1], 제작자의 애매한 느낌을 퍼지 논리를 이용하여 표현하는 방법, 이미지를 와핑하는 방법, 여러 단계의 벡터 필드 변환을 이용하는 방법등이 연구되어 왔다. 본 논문에서는 실시간 또는 준비된 영상을 입력으로 받아 저장한 후, 네 단계의 과정으로 처리한 후 최종적으로 캐리커처된 이미지를 생성하게 된다. 각 단계별 처리 내용으로는 첫번째 단계에서는 영상에서 얼굴을 검출하고 두번째 단계에서는 특정 얼굴부위의 기하학적 정보를 좌표값으로 추출한다. 세번째 단계에서는 전 단계에서 얻은 좌표값으로 로컬 와핑 기법을 이용하여 영상을 변환한다. 네 번째 단계에서는 변형된 영상으로 퍼지 논리를 이용하여 보다 개선된 윤곽선 이미지로 변환하여 캐리커처 이미지를 얻는다. 본 논문에서는 영상 인식, 변환 및 윤곽선 검출 및 둥의 여러 가지 영상 처리 기법을 이용하여 기존의 캐리커처 제작 방식보다 간단하고, 복잡한 연산 과정이 없는 캐리커처 제작 시스템을 구현하였다.

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