• 제목/요약/키워드: Removed object

검색결과 155건 처리시간 0.197초

라돈 변환을 이용한 회전된 물체의 효율적인 보정 (Efficient Correction of a Rotated Object Using Radon Transform)

  • 조보호;정성환
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권3호
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    • pp.291-295
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    • 2008
  • 본 논문은 비전 시스템을 통하여 입력되어 들어오는 회전된 물체를 보정하기 위해 사용하는 선 구조 분석 도구인 라돈변환의 문제점을 해결하기 위해 입력 영상 간소화 방법을 제안한다. 먼저, 비전 시스템을 통하여 입력된 영상 내에서 불필요한 배경 부분을 제거하여 물체 영상을 추출한다. 다음, 추출된 물체 영상에 대하여 기울기를 고려하여 제한된 물체 영상만을 라돈 변환의 최종 입력 영상으로 추출한다. 마지막으로 최종 입력 영상에 대하여 라돈 변환을 사용하여 회전각을 추출한 후, 원 영상 내의 회전된 물체를 보정한다. 실험 결과, 제안한 방법은 처리 속도를 약 64% 향상시킬 수 있었고, 기억용량은 약 18% 줄일 수 있었으며, 선 검출율은 약 18%까지 향상시킬 수 있었다.

효과적인 이동물체 추적을 위한 색도 영상과 엔트로피 기반의 그림자 제거 (Shadow Removal Based on Chromaticity and Entropy for Efficient Moving Object Tracking)

  • 박기홍
    • 한국항행학회논문지
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    • 제18권4호
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    • pp.387-392
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    • 2014
  • 최근 지능형 비디오 감시를 위한 다양한 연구가 제안되고 있음에도 CCTV 영상에서 이상 징후 판단이 사람에 의해 이루어지고 있어 상황인식을 위한 방법 및 연구가 필요하다. 본 논문에서는 이동물체 검출 및 추적을 위해 RGB 칼라 모델 기반의 색도 영상과 엔트로피 영상을 도출하여 그림자 제거를 수행한 후 이동물체를 추적하는 방법을 제안한다. 이동물체 검출을 위해 잡음 및 주위환경변화에 민감하지만 순간적으로 발생되는 상황인지 환경에서 효과적인 차영상 모델을 적용하였다. 검출한 이동물체 영역에서 RGB 채널의 색도 영상을 기반으로 첫 번째 그림자 후보 영역을 선정하였고, 그레이레벨에서 엔트로피를 계산하여 두 번째 그림자 후보 영역을 추정하여 그림자를 제거하였다. 제안하는 방법의 타당성을 위해 고속도로에서 주행하는 자동차들을 대상으로 실험하였고, 실험 결과 색상과 엔트로피를 이용한 그림자를 제거와 이동물체 추적이 효과적으로 수행됨을 확인하였다.

초음파 영상에서 LoG 연산자를 이용한 진단 객체의 3차원 분할 (3D Segmentation of a Diagnostic Object in Ultrasound Images Using LoG Operator)

  • 정말남;곽종인;김상현;김남철
    • 대한의용생체공학회:의공학회지
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    • 제24권4호
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    • pp.247-257
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    • 2003
  • This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

Surface Approximation Utilizing Orientation of Local Surface

  • Ko, Myeong-Cheol;Sohn, Won-Sung;Choy, Yoon-Chul
    • 한국멀티미디어학회논문지
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    • 제6권4호
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    • pp.698-706
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    • 2003
  • The primary goal of surface approximation is to reduce the degree of deviation of the simplified surface from the original surface. However it is difficult to define the metric that can measure the amount of deviation quantitatively. Many of the existing studies analogize it by using the change of the scalar quantity before and after simplification. This approach makes a lot of sense in the point that the local surfaces with small scalar are relatively less important since they make a low impact on the adjacent areas and thus can be removed from the current surface. However using scalar value alone there can exist many cases that cannot compute the degree of geometric importance of local surface. Especially the perceptual geometric features providing important clues to understand an object, in our observation, are generally constructed with small scalar value. This means that the distinguishing features can be removed in the earlier stage of the simplification process. In this paper, to resolve this problem, we present various factors and their combination as the metric for calculating the deviation error by introducing the orientation of local surfaces. Experimental results indicate that the surface orientation has an important influence on measuring deviation error and the proposed combined error metric works well retaining the relatively high curvature regions on the object's surface constructed with various and complex curvatures.

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도시철도 환경에 적합한 지능형 감시카메라 시나리오의 연구 (A Study of Scenario in Intelligent Surveillance Camera for Urban Transit)

  • 장일식;정철준;김형민;안태기;박구만
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2009년도 춘계학술대회 논문집
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    • pp.866-871
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    • 2009
  • In this paper, we introduced design of intelligent surveillance camera system and typical event processing scenario for urban transit. To analyze video, we studied events that frequently occur in surveillance camera system. Scenario is designed for estimation in the case of seven representative situations(designated area invasion, an object left alone, removed object in designated area, object tracking, loitering and congestion measurement) in urban transit. Our system is optimized for low hardware complexity, real time processing and scenario dependent solution.

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Animal Tracking in Infrared Video based on Adaptive GMOF and Kalman Filter

  • Pham, Van Khien;Lee, Guee Sang
    • 스마트미디어저널
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    • 제5권1호
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    • pp.78-87
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    • 2016
  • The major problems of recent object tracking methods are related to the inefficient detection of moving objects due to occlusions, noisy background and inconsistent body motion. This paper presents a robust method for the detection and tracking of a moving in infrared animal videos. The tracking system is based on adaptive optical flow generation, Gaussian mixture and Kalman filtering. The adaptive Gaussian model of optical flow (GMOF) is used to extract foreground and noises are removed based on the object motion. Kalman filter enables the prediction of the object position in the presence of partial occlusions, and changes the size of the animal detected automatically along the image sequence. The presented method is evaluated in various environments of unstable background because of winds, and illuminations changes. The results show that our approach is more robust to background noises and performs better than previous methods.

Adaptive Object-Region-Based Image Pre-Processing for a Noise Removal Algorithm

  • Ahn, Sangwoo;Park, Jongjoo;Luo, Linbo;Chong, Jongwha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권12호
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    • pp.3166-3179
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    • 2013
  • A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filters can be applied to other regions to reduce overall computational complexity. In the proposed method, bright region segmentation is performed, followed by segmentation of object and background regions. Noise in dark, background, and object regions is then removed by the median, fast bilateral, and bilateral filters, respectively. Simulations show that the proposed algorithm is much faster than and performs nearly as well as the bilateral filter (which is considered a powerful noise removal algorithm); it reduces computation time by 19.4 % while reducing PSNR by only 1.57 % relative to bilateral filtering. Thus, the proposed algorithm remarkably reduces computation while maintaining accuracy.

Pre-Hospital and In-Hospital Management of an Abdominal Impalement Injury Caused by a Tree Branch

  • Ahn, So Ra;Lee, Joo Hyun;Kim, Keun Young;Park, Chan Yong
    • Journal of Trauma and Injury
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    • 제34권4호
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    • pp.288-293
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    • 2021
  • In South Korea, most patients who visit trauma centers with abdominal injuries have blunt trauma, and penetrating injuries are relatively rare. In extremely rare cases, some patients are admitted with a long object penetrating their abdomen, and these injuries are referred to as abdominal impalement injuries. Most cases of impalement injuries lead to fatal bleeding, and patients often die at the scene of the accident. However, patients who survive until reaching the hospital can have a good prognosis with optimal treatment. A 68-year-old female patient was admitted to the trauma center with a 4-cm-thick tree branch impaling her abdomen. The patient was transported by a medical helicopter and had stable vital signs at admission. The branch sticking out of the abdomen was quite long; thus, we carefully cut the branch with an electric saw to perform computed tomography (CT). CT revealed no signs of major blood vessel injury, but intestinal perforation was observed. During laparotomy, the tree branch was removed after confirming that there were no vascular injuries, and enterostomy was performed because of extensive intestinal injury. After treating other injuries, the patient was discharged without any complications except colostomy. Abdominal impalement injuries are treated using various approaches depending on the injury mechanism and injured region. However, the most important consideration is that the impaled object should not be removed during transportation and resuscitation. Instead, it should only be removed after checking for injuries to blood vessels during laparotomy in an environment where injury control is possible.

배경을 제외한 영상에서 명암과 특징을 기반으로하는 스테레오 정합 (Stereok Matching based on Intensity and Features for Images with Background Removed)

  • 최태은;권혁민;박종승;한준희
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권12호
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    • pp.1482-1496
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    • 1999
  • 기존의 스테레오 정합 알고리즘은 크게 명암기반기법과 특징기반기법의 두 가지로 나눌 수 있다. 그리고, 각 기법은 그들 나름대로의 장단점을 갖는다. 본 논문은 이 두 기법을 결합하는 새로운 알고리즘을 제안한다. 본 논문에서는 물체모델링을 목적으로 하기 때문에 배경을 제거하여 정합하는 방법을 사용한다. 이를 위해, 정합요소들과 정합유사함수가 정의되고, 정합유사함수는 두 기법사이의 장단점을 하나의 인수에 의해 조절한다. 그 외에도 거리차 지도의 오류를 제거하는 coarse-to-fine기법, 폐색문제를 해결하는 다중윈도우 기법을 사용하였고, 물체의 표면형태를 알아내기 위해 morphological closing 연산자를 이용하여 물체와 배경을 분리하는 방법을 제안하였다. 이러한 기법들을 기반으로 하여 여러가지 영상에 대해 실험을 수행하였으며, 그 결과들은 본 논문이 제안하는 기법의 효율성을 보여준다. 정합의 결과로 만들어지는 거리차 지도는 3차원 모델링을 통해 가상공간상에서 보여지도록 하였다.Abstract Classical stereo matching algorithms can be classified into two major areas; intensity-based and feature-based stereo matching. Each technique has advantages and disadvantages. This paper proposes a new algorithm which merges two main matching techniques. Since the goal of our stereo algorithm is in object modeling, we use images for which background is removed. Primitives and a similarity function are defined. The matching similarity function selectively controls the advantages and disadvantages of intensity-based and feature-based matching by a parameter.As an additional matching strategy, a coarse-to-fine method is used to remove a errorneous data on the disparity map. To handle occlusions, multiple windowing method is used. For finding the surface shape of an object, we propose a method that separates an object and the background by a morphological closing operator. All processes have been implemented and tested with various image pairs. The matching results showed the effectiveness of our method. From the disparity map computed by the matching process, 3D modeling is possible. 3D modeling is manipulated by VRML(Virtual Reality Manipulation Language). The results are summarized in a virtual reality space.

웨이브렛 형태학 알고리즘 적용한 객체 분할의 클러스터링 분석 (Clustering Analysis of Object Segmentation applying Wavelet Morphology)

  • 백덕수;변오성;강창수
    • 전자공학회논문지 IE
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    • 제43권2호
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    • pp.39-48
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    • 2006
  • 본 논문은 공간적 자동 객체 분할의 개념과 클러스터링 개념을 가진 웨이브렛 형태학 알고리즘을 제안하였다. 제안된 알고리즘을 이용하여 컬러 얼굴을 분할할 때 영상을 단순화하였으며, 또한 사용자의 조작 없이 실시간적으로 분할해 검출할 수 있도록 공간적 특성을 이용하였다. 이것은 HSV 컬러 모델을 이용하여 영상에서 잡음으로 간주되는 작은 부분을 제거하고, 얼굴영상 이외의 부분을 제거하기 위해 웨이브렛 형태학을 적용하였다. 본 논문은 웨이브렛 형태학 알고리즘과 형태학 알고리즘을 비교하였으며, 그리고 HSV 컬러 공간 모델을 적용한 영상에서 얼굴 객체 부분을 정확하게 검출함을 보였다.