• Title/Summary/Keyword: 윤곽 검출

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A study on Object Contour Detection using improved Dual Active Contour Model (개선된 Dual Active Contour Model을 이용한 물체 윤곽선 검출에 관한 연구)

  • 문창수;유봉길;이웅기
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.1
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    • pp.81-94
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    • 1998
  • In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes". Snakes is a model which defines the contour of image energy. It also can find the contour of object by minimizing these energy functions. The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initialization. and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of 8$\times$8 size at each contour point consisting Snakes in order to solve these problems. The method offered in this paper is applied to extract the contour of original image and cup image added to gaussian noise. By tracking the face using this offered method, it is applied to virtual reality and motion tracking. tracking.

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Automation of Snake for Extraction of Multi-Object Contours from a Natural Scene (자연배경에서 여러 객체 윤곽선의 추출을 위한 스네이크의 자동화)

  • 최재혁;서경석;김복만;최흥문
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.6
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    • pp.712-717
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    • 2003
  • A novel multi-snake is proposed for efficient extraction of multi-object contours from a natural scene. An NTGST(noise-tolerant generalized symmetry transform) is used as a context-free attention operator to detect and locate multiple objects from a complex background and then the snake points are automatically initialized nearby the contour of each detected object using symmetry map of the NTGST before multiple snakes are introduced. These procedures solve the knotty subjects of automatic snake initialization and simultaneous extraction of multi-object contours in conventional snake algorithms. Because the snake points are initialized nearby the actual contour of each object, as close as possible, contours with high convexity and/or concavity can be easily extracted. The experimental results show that the proposed method can efficiently extract multi-object contours from a noisy and complex background of natural scenes.

Face Detection for Automatic Avatar Creation by using Deformable Template and GA (Deformable Template과 GA를 이용한 얼굴 인식 및 아바타 자동 생성)

  • Park Tae-Young;Kwon Min-Su;Kang Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.1
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    • pp.110-115
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    • 2005
  • This paper proposes the method to detect contours of a face, eyes and a mouth in a color image for making an avatar automatically. First, we use the HSI color model to exclude the effect of various light condition, and we find skin regions in an input image by using the skin color is defined on HS-plane. And then, we use deformable templates and Genetic Algorithm(GA) to detect contours of a face, eyes and a mouth. Deformable templates consist of B-spline curves and control point vectors. Those can represent various shape of a face, eyes and a mouth. And GA is very useful search procedure based on the mechanics of natural selection and natural genetics. Second, an avatar is created automatically by using contours and Fuzzy C-means clustering(FCM). FCM is used to reduce the number of face color As a result, we could create avatars like handmade caricatures which can represent the user's identity, differing from ones generated by the existing methods.

Lung Detection by Using Geodesic Active Contour Model Based on Characteristics of Lung Parenchyma Region (폐실질 영역 특성에 기반한 지오데식 동적 윤곽선 모델을 이용한 폐영역 검출)

  • Won Chulho;Lee Seung-Ik;Lee Jung-Hyun;Seo Young-Soo;Kim Myung-Nam;Cho Jin-Ho
    • Journal of Korea Multimedia Society
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    • v.8 no.5
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    • pp.641-650
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    • 2005
  • In this parer, curve stopping function based on the CT number of lung parenchyma from CT lung images is proposed to detect lung region in replacement of conventional edge indication function in geodesic active contour model. We showed that the proposed method was able to detect lung region more effectively than conventional method by applying three kinds of measurement numerically. And, we verified the effectiveness of proposed method visually by observing the detection Procedure on actual CT images. Because lung parenchyma region could be precisely detected from actual EBCT (electron beam computer tomography) lung images, we were sure that the Proposed method could aid to early diagnosis of lung disease and local abnormality of function.

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SIFT based Image Similarity Search using an Edge Image Pyramid and an Interesting Region Detection (윤곽선 이미지 피라미드와 관심영역 검출을 이용한 SIFT 기반 이미지 유사성 검색)

  • Yu, Seung-Hoon;Kim, Deok-Hwan;Lee, Seok-Lyong;Chung, Chin-Wan;Kim, Sang-Hee
    • Journal of KIISE:Databases
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    • v.35 no.4
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    • pp.345-355
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    • 2008
  • SIFT is popularly used in computer vision application such as object recognition, motion tracking, and 3D reconstruction among various shape descriptors. However, it is not easy to apply SIFT into the image similarity search as it is since it uses many high dimensional keypoint vectors. In this paper, we present a SIFT based image similarity search method using an edge image pyramid and an interesting region detection. The proposed method extracts keypoints, which is invariant to contrast, scale, and rotation of image, by using the edge image pyramid and removes many unnecessary keypoints from the image by using the hough transform. The proposed hough transform can detect objects of ellipse type so that it can be used to find interesting regions. Experimental results demonstrate that the retrieval performance of the proposed method is about 20% better than that of traditional SIFT in average recall.

SCLC-Edge Detection Algorithm for Skin Cancer Classification (피부암 병변 분류를 위한 SCLC-Edge 검출 알고리즘)

  • June-Young Park;Chang-Min Kim;Roy C. Park
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.4
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    • pp.256-263
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    • 2022
  • Skin cancer is one of the most common diseases in the world, and the incidence rate in Korea has increased by about 100% over the past five years. In the United States, more than 5 million people are diagnosed with skin cancer every year. Skin cancer mainly occurs when skin tissue is damaged for a long time due to exposure to ultraviolet rays. Melanoma, a malignant tumor of skin cancer, is similar in appearance to Atypical melanocytic nevus occurring on the skin, making it difficult for the general public to be aware of it unless secondary signs occur. In this paper, we propose a skin cancer lesion edge detection algorithm and a deep learning model, CRNN, which performs skin cancer lesion classification for early detection and classification of these skin cancers. As a result of the experiment, when using the contour detection algorithm proposed in this paper, the classification accuracy was the highest at 97%. For the Canny algorithm, 78% was shown, 55% for Sobel, and 46% for Laplacian.

Kidney's feature point extraction based on edge detection using SIFT algorithm in ultrasound image (Edge detection 기반의 SIFT 알고리즘을 이용한 kidney 특징점 검출 방법)

  • Kim, Sung-Jung;Yoo, JaeChern
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.89-90
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    • 2019
  • 본 논문에서는 ultrasound image Right Parasagittal Liver에 edge detection을 적용한 후, 특징점 검출 알고리즘인 Scale Invarient Feature Transfom(SIFT)를 이용하여 특징점의 위치를 살펴보도록 한다. edge detection 알고리즘으로는 Canny edge detection과 Prewitt edge detection을 적용하기로 한다.

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Video Segmentation and Video Browsing using the Edge and Color Distribution (윤곽선과 컬러 분포를 이용한 비디오 분할과 비디오 브라우징)

  • Heo, Seoung;Kim, Woo-Saeng
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.9
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    • pp.2197-2207
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    • 1997
  • In this paper, we propose a video data segmentation method using edge and color distribution of video frames and also develop a video browser by using the proposed algorithm. To segment a video, we use a 644-bin HSV color histogram and the edge information which generated with automatic threshold method. We consider scene's characteristics by using positions and colo distributions of object in each frame. We develop a hierarchical and a shot-based browser for video browsing. We also show that our proposed method is less sensitive to light effects and more robust to motion effects than previous ones like a histogram-based method by testing with various video data.

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Automatic Boundary Detection from 3D Cloud Points Using Color Image (칼라영상을 이용한 3차원 점군데이터 윤곽선 자동 검출)

  • Kim, Nam-Woon;Roh, Yi-Ju;Jeong, Hee-Seok;Jeong, Joong-Yeon;Jung, Kyeong-Hoon;Kang, Dong-Wook;Kim, Ki-Doo
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.141-142
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    • 2008
  • 본 논문은 텍스처된 3차원 점군데이터를 효율적으로 모델링하는 방법을 제안한다. 지상라이다로부터 획득한 3차원 점군데이터는 많은 노이즈를 가지고 있으며 이로 인해 자동적인 모델링이 어렵다. 3차원 모델링에 있어서 메쉬를 생성해야 3차원 랜더링이 가능하지만 3차원 메쉬 생성은 노이즈에 취약하기 때문에 디자이너들이 수작업으로 노이즈를 제거해야만 한다. 하지만 노이즈 자제가 지상 라이다로부터 들어온 데이터이기 때문에 자동적인 노이즈 제거가 어렵다. 본 논문에서는 텍스처된 지상 라이다 데이터로부터 칼라 영상의 정보를 이용한 윤곽선 정보 검출 방법을 제안한다. 대부분의 건물과 같은 구조물에서 최 외곽은 같은 색의 정보를 가지고 있다. 최 외곽 칼라의 정보를 이용하여 칼라 정보의 변화를 제한하고, 유사 칼라 정보를 가지고 있는 픽셀만 얻어냄으로써 최외각 정보를 얻어낸다. 칼라 이미지를 이용만 필터링 된 점군데이터는 xy, xz, yz 각각의 평면에서 윤곽선 데이터를 가지며 이는 구조물에 대한 모델링의 속도를 빠르게 해준다.

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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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