• Title/Summary/Keyword: Edge extraction

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Simplified Representation of Image Contour

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.6 no.4
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    • pp.317-322
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    • 2018
  • We use edge detection technique for the input image to extract the entire edges of the object in the image and then select only the edges that construct the outline of the object. By examining the positional relation between these pixels composing the outline, a simplified version of the outline of the object in the input image is generated by removing unnecessary pixels while maintaining the condition of connection of the outline. For each pixel constituting the outline, its direction is calculated by examining the positional relation with the next pixel. Then, we group the consecutive pixels with same direction into one and then change them to a line segment instead of a point. Among those line segments composing the outline of the object, a line segment whose length is smaller than a predefined minimum length of acceptable line segment is removed by merging it into one of the adjacent line segments. As a result, an outline composed of line segments of over a certain length is obtained through this process.

Extraction of Collaborative Execution Path between Local and Edge Server in an FEC Environment (FEC 환경에서 로컬과 에지 서버 간의 협업 실행경로 추출)

  • Baik, Jae-seok;Nam, Kwang-Woo;Jang, Min-seok;Lee, Yon-sik
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.625-627
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    • 2022
  • FEC (Fog/Edge Computing) 환경에서 지연시간 최소화는 로컬과 에지 서버 간의 효율적인 협력을 보장하기 위한 최적의 계산 오프로딩 방법 결정을 통해 실현될 수 있다. 본 논문은 임의의 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 로컬(모바일 장치)과 에지 서버 간의 협업 경로를 추출하는 방법을 제안한다. 제안 방법은 다중 분기구조를 포함하는 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 최적 협업 실행경로 추출 방법을 제안한다. 제안 방법은 각 부분 모듈들의 실행위치에 따라 변화되는 지연시간 측정 및 분석에 적용가능하다.

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Skew Compensation and Text Extraction of The Traffic Sign in Natural Scenes (자연영상에서 교통 표지판의 기울기 보정 및 덱스트 추출)

  • Choi Gyu-Dam;Kim Sung-Dong;Choi Ki-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.3 no.2 s.5
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    • pp.19-28
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    • 2004
  • This paper shows how to compensate the skew from the traffic sign included in the natural image and extract the text. The research deals with the Process related to the array image. Ail the process comprises four steps. In the first fart we Perform the preprocessing and Canny edge extraction for the edge in the natural image. In the second pan we perform preprocessing and postprocessing for Hough Transform in order to extract the skewed angle. In the third part we remove the noise images and the complex lines, and then extract the candidate region using the features of the text. In the last part after performing the local binarization in the extracted candidate region, we demonstrate the text extraction by using the differences of the features which appeared between the tett and the non-text in order to select the unnecessary non-text. After carrying out an experiment with the natural image of 100 Pieces that includes the traffic sign. The research indicates a 82.54 percent extraction of the text and a 79.69 percent accuracy of the extraction, and this improved more accurate text extraction in comparison with the existing works such as the method using RLS(Run Length Smoothing) or Fourier Transform. Also this research shows a 94.5 percent extraction in respect of the extraction on the skewed angle. That improved a 26 percent, compared with the way used only Hough Transform. The research is applied to giving the information of the location regarding the walking aid system for the blind or the operation of a driverless vehicle

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Vision Based Vehicle Detection and Traffic Parameter Extraction (비젼 기반 차량 검출 및 교통 파라미터 추출)

  • 하동문;이종민;김용득
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.11
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    • pp.610-620
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    • 2003
  • Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 96%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.

Automated radiation field edge detection in portal image using optimal threshold value (최적 문턱치 설정을 이용한 포탈영상에서의 자동 에지탐지 기법에 관한 연구)

  • 허수진
    • Journal of Biomedical Engineering Research
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    • v.16 no.3
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    • pp.337-344
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    • 1995
  • Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

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Reconstruction from Feature Points of Face through Fuzzy C-Means Clustering Algorithm with Gabor Wavelets (FCM 군집화 알고리즘에 의한 얼굴의 특징점에서 Gabor 웨이브렛을 이용한 복원)

  • 신영숙;이수용;이일병;정찬섭
    • Korean Journal of Cognitive Science
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    • v.11 no.2
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    • pp.53-58
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    • 2000
  • This paper reconstructs local region of a facial expression image from extracted feature points of facial expression image using FCM(Fuzzy C-Meang) clustering algorithm with Gabor wavelets. The feature extraction in a face is two steps. In the first step, we accomplish the edge extraction of main components of face using average value of 2-D Gabor wavelets coefficient histogram of image and in the next step, extract final feature points from the extracted edge information using FCM clustering algorithm. This study presents that the principal components of facial expression images can be reconstructed with only a few feature points extracted from FCM clustering algorithm. It can also be applied to objects recognition as well as facial expressions recognition.

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Feature-Point Extraction by Dynamic Linking Model bas Wavelets and Fuzzy C-Means Clustering Algorithm (Gabor 웨이브렛과 FCM 군집화 알고리즘에 기반한 동적 연결모형에 의한 얼굴표정에서 특징점 추출)

  • 신영숙
    • Korean Journal of Cognitive Science
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    • v.14 no.1
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    • pp.11-16
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    • 2003
  • This Paper extracts the edge of main components of face with Gator wavelets transformation in facial expression images. FCM(Fuzzy C-Means) clustering algorithm then extracts the representative feature points of low dimensionality from the edge extracted in neutral face. The feature-points of the neutral face is used as a template to extract the feature-points of facial expression images. To match point to Point feature points on an expression face against each feature point on a neutral face, it consists of two steps using a dynamic linking model, which are called the coarse mapping and the fine mapping. This paper presents an automatic extraction of feature-points by dynamic linking model based on Gabor wavelets and fuzzy C-means(FCM) algorithm. The result of this study was applied to extract features automatically in facial expression recognition based on dimension[1].

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A Study For Automobile License Plate Extraction Using DCT and Correlation (DCT와 Correlation을 이용한 자동차번호판 추출에 관한 연구)

  • 경보현;손태주;남궁연;남궁재찬
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.7A
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    • pp.1050-1056
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    • 2000
  • In this paper, We Propose the automobile license plate extraction method using Discrete Cosin Transform and Correlation fem automobile image obtained through digital camera. The automobile license plate is consisted of the character and rectangle background of it. We extracted the automobile edge image by the DCT processing of automobile image and Obtained the automobile license plate from the automobile edge image by Correlation processing. We separated characters from automobile license plate using the projection histogram. Compare to the previous methods, we obtained the good result from extracting the automobile license plate at night, very strong light and bad weather.

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Removal of the Ambiguity of Images by Normalization and Entropy Minimization and Edge Detection by Understanding of Image Structures (정규화와 엔트로피의 최소화에 의한 영상 경계의 애매성 제거 및 영상 구조 파악에 의한 경계선 추출)

  • Jo, Dong-Uk;Baek, Seung-Jae
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.9
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    • pp.2558-2562
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    • 1999
  • This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.

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