• 제목/요약/키워드: Edge extraction

검색결과 496건 처리시간 0.03초

영역기반 계단응답 추출 및 디지털자동초점을 위한 점확산함수 추정 (Region-Based Step-Response Extraction and PSF Estimation for Digital Auto-Focusing)

  • 박영욱;김동균;이진희;백준기
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.827-828
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    • 2008
  • Blur identification is the first and the most important step of restoring images. Edge region of the image usually conveys important information of blur parameters. In this paper we propose a region-based edge extraction method for estimating point-spread-function (PSF). As a result, the proposed method can detect the starting and the ending points of a step response, and provides the PSF parameters to the restoration process.

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러프 집합 이론을 이용한 3차원 물체 특징 추출 (3D Feature Detection using Rough Set Theory)

  • 정영준;전효병;심귀보
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2222-2224
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    • 1998
  • This paper presents a 3D feature extraction method using rough set theory. Using the stereo cameras, we obtain the raw images and then perform several processes including gradient computation and image matching process. Decision rule constructed via rough set theory determines whether a ceratin point in the image is 3D edge or not. We propose a method finding rules for 3D edge extraction using rough set.

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SEGMENTATION AND EXTRACTION OF TEETH FROM 3D CT IMAGES

  • Aizawa, Mitsuhiro;Sasaki, Keita;Kobayashi, Norio;Yama, Mitsuru;Kakizawa, Takashi;Nishikawa, Keiichi;Sano, Tsukasa;Murakami, Shinichi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.562-565
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    • 2009
  • This paper describes an automatic 3-dimensional (3D) segmentation method for 3D CT (Computed Tomography) images using region growing (RG) and edge detection techniques. Specifically, an augmented RG method in which the contours of regions are extracted by a 3D digital edge detection filter is presented. The feature of this method is the capability of preventing the leakage of regions which is a defect of conventional RG method. Experimental results applied to the extraction of teeth from 3D CT data of jaw bones show that teeth are correctly extracted by the proposed method.

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Pan-sharpening Effect in Spatial Feature Extraction

  • Han, Dong-Yeob;Lee, Hyo-Seong
    • 대한원격탐사학회지
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    • 제27권3호
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    • pp.359-367
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    • 2011
  • A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

캐니 에지 검출을 이용한 해삼의 특징점 추출 (Feature Point Extraction of Sea Cucumbers using Canny Edge Detection)

  • 이건익;우영배;민준식;최철재
    • 한국전자통신학회논문지
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    • 제13권6호
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    • pp.1281-1286
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    • 2018
  • 세계적으로 1500 종 이상이 분포하고 있는 해삼은 오랫동안 여러 나라에서 중요한 수산 자원으로 취급되어져 왔고 개체군 보존관리 보호종에 속하는 고부가가치 품종이다. 해삼에 관한 연구는 음식과 추출물의 효능에 관한 것이 대부분이며, 아직까지 해삼 특징 식별에 대한 연구는 이루어지지 않고 있다. 이에 본 연구는 고부가가치 품종인 해삼을 대량으로 포획하기 위하여 해삼의 특징점 추출을 위한 경계 검출 알고리즘을 제안하였으며 향후 해삼 인식 프로그램에 많은 도움이 되리라 생각한다.

수리형태학적 Laplacian 연산을 이용한 새로운 동영상 Detail 추출 방법 (A NEW DETAIL EXTRACTION TECHNIQUE FOR VIDEO SEQUENCE CODING USING MORPHOLOGICAL LAPLACIAN OPERATOR)

  • 어진우;김희준
    • 전기전자학회논문지
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    • 제4권2호
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    • pp.288-294
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    • 2000
  • 본 논문에서는 동영상 압축 기법을 향상시키기 위하여 효율적인 detail 추출 기법을 제안한다. 기존의 top-hat 변환을 이용한 기법은 고립되어 있고 시각적으로 중요한 detail의 추출에는 효율적이지만, 영역의 경계에서는 비효율적이다. 제안된 기법은 수리형태학적 Laplacian 연산의 영역경계 정보추출의 성질을 이용하여 압축을 향상시키고 저비트율을 제공한다. 실험결과를 통해서 제안된 기법이 기존 기법보다 효율적임을 보이고 수리형태학적 Laplacian 연산 적용의 타당성을 설명한다.

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경면 다면체의 모서리 추출 (Extracting roof edges of specular polyhedra)

  • 박원식;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.379-382
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    • 1997
  • This paper introduces a new vision technique for extracting roof edges of polyhedra having specularly reflecting surfaces. There have been many previous works on object recognition using edge information. But they can not be applied to specular objects since it is hard to acquire reliable camera images of specular objects. If there is a method which can extract the edges of specular objects, it is possible to apply edge-based recognition algorithms to specular objects. To acquire the reliable edge images of specular objects, scanned double pass retroreflection method is proposed, whose main physical characteristic is curvature-sensitive. This utility of the physical characteristic is motivated by the idea that roof edges can be characterized as local surfaces of high curvature. In this paper, the optical characteristics of double pass retroreflection are discussed and a series of simulation studies are performed to verify and analyze the sensor characteristics. The results from a series of simulations show the effectiveness of the proposed method.

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스펙트럼 패턴 기반의 잡음 환경에 강인한 음성의 끝점 검출 기법 (Spectral Pattern Based Robust Speech Endpoint Detection in Noisy Environments)

  • 박진수;이윤재;이인호;고한석
    • 말소리와 음성과학
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    • 제1권4호
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    • pp.111-117
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    • 2009
  • In this paper, a new speech endpoint detector in noisy environment is proposed. According to the previous research, the energy feature in the speech region is easily distinguished from that in the speech absent region. In conventional method, the endpoint can be found by applying the edge detection filter that finds the abrupt changing point in feature domain. However, since the frame energy feature is unstable in noisy environment, the accurate edge detection is not possible. Therefore, in this paper, the novel feature extraction method based on spectrum envelop pattern is proposed. Then, the edge detection filter is applied to the proposed feature for detection of the endpoint. The experiments are performed in the car noise environment and a substantial improvement was obtained over the conventional method.

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토폴로지 정보가 없는 CAD 곡면의 꺾인 모서리 탐색 (Convex Sharp Edge Detection of CAD Surfaces without Topology)

  • 박정환;이정근
    • 한국정밀공학회지
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    • 제17권2호
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    • pp.73-79
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    • 2000
  • The part-surface of mold or stamping-dies consists of a compound surface which consists of lots of composite surfaces, and may have various types of feature shapes including convex sharp edge (CSE). Those CSE features should be considered with care in machining the surface, which necessitates extraction of CSE curves on a compound surface. This work can be done rather easily for a solid model which has a complete topology information. In case of the compound surface without topology information, however, such CSE curves must be gathered through some geometrical calculations paying much computation time. In the paper, extracting CSE curves by the construction of a CSE region-map which can reduce time, and detecting various common edge types are presented.

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도로영상의 잡음도 식별을 위한 퍼지신경망 알고리즘 (A Fuzzy Neural-Network Algorithm for Noisiness Recognition of Road Images)

  • 이준웅
    • 한국자동차공학회논문집
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    • 제10권5호
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    • pp.147-159
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    • 2002
  • This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.