• Title/Summary/Keyword: 자동 촬영

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Development of a Lane Detect Algorithm from Road-Facing Cameras on a Vehicle (차량에 부착된 측하방 CCD카메라를 이용한 차선추출 알고리즘 개발)

  • Rhee, Soo-Ahm;Lee, Tae-Yoon;Kim, Tae-Jung;Sung, Jung-Gon
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.3 s.33
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    • pp.87-94
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    • 2005
  • 3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

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Automatic Lung Registration using Local Distance Propagation (지역적 거리전파를 이용한 자동 폐 정합)

  • Lee Jeongjin;Hong Helen;Shin Yeong Gil
    • Journal of KIISE:Software and Applications
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    • v.32 no.1
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    • pp.41-49
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    • 2005
  • In this Paper, we Propose an automatic lung registration technique using local distance propagation for correcting the difference between two temporal images by a patient's movement in abdomen CT image obtained from the same patient to be taken at different time. The proposed method is composed of three steps. First, lung boundaries of two temporal volumes are extracted, and optimal bounding volumes including a lung are initially registered. Second, 3D distance map is generated from lung boundaries in the initially taken volume data by local distance propagation. Third, two images are registered where the distance between two surfaces is minimized by selective distance measure. In the experiment, we evaluate a speed and robustness using three patients' data by comparing chamfer-matching registration. Our proposed method shows that two volumes can be registered at optimal location rapidly. and robustly using selective distance measure on locally propagated 3D distance map.

Face Recognition Using Automatic Face Enrollment and Update for Access Control in Apartment Building Entrance (아파트 공동현관 출입 통제를 위한 자동 얼굴 등록 및 갱신 기반 얼굴인식)

  • Lee, Seung Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1152-1157
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    • 2021
  • This paper proposes a face recognition method for access control of apartment building. Different from most existing face recognition methods, the proposed one does not require any manual process for face enrollment. When a person is exiting through the main entrance door, his/her face data (i.e., face image and face feature) are automatically extracted from the captured video and registered in the database. When the person needs to enter the building again, the face data are extracted and the corresponding face feature is compared with the face features registered in the database. If a matching person exists, the entrance door opens and his/her access is allowed. The face data of the matching person are immediately deleted and the database has the latest face data of outgoing person. Thus, a higher recognition accuracy could be expected. To verify the feasibility of the proposed method, Python based face recognition has been implemented and the cloud service provided by a web portal.

Application of Computer-Aided Diagnosis for the Differential Diagnosis of Fatty Liver in Computed Tomography Image (전산화단층촬영 영상에서 지방간의 감별진단을 위한 컴퓨터보조진단의 응용)

  • Park, Hyong-Hu;Lee, Jin-Soo
    • Journal of the Korean Society of Radiology
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    • v.10 no.6
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    • pp.443-450
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    • 2016
  • In this study, we are using a computer tomography image of the abdomen, as an experimental linear research for the image of the fatty liver patients texture features analysis and computer-aided diagnosis system of implementation using the ROC curve analysis, from the computer tomography image. We tried to provide an objective and reliable diagnostic information of fatty liver to the doctor. Experiments are usually a fatty liver, via the wavelet transform of the abdominal computed tomography images are configured with the experimental image section, shows the results of statistical analysis on six parameters indicating a feature value of the texture. As a result, the entropy, average luminance, strain rate is shown a relatively high recognition rate of 90% or more, the control also, flatness, uniformity showed relatively low recognition rate of about 70%. ROC curve analysis of six parameters are all shown to 0.900 (p = 0.0001) or more, showed meaningful results in the recognition of the disease. Also, to determine the cut-off value for the prediction of disease six parameters. These results are applicable from future abdominal computed tomography images as a preliminary diagnostic article of diseases automatic detection and eventual diagnosis.

The Comparative Analysis of Exposure Conditions between F/S and C/R System for an Ideal Image in Simple Abdomen (복부 단순촬영의 이상적 영상구현을 위한 F. S system과 C.R system의 촬영조건 비교분석)

  • Son, Sang-Hyuk;Song, Young-Geun;Kim, Je-Bong
    • Korean Journal of Digital Imaging in Medicine
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    • v.9 no.1
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    • pp.37-43
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    • 2007
  • 1. Purpose : This study is to present effective exposure conditions to acquire the best image of simple abdomen in Film Screen (F.S) system and Computed Radiography (C.R) system. 2. Method : In the F.S system, while an exposure condition was fixed as 70kVp, images of a patients simple abdomen were taken under the different mAs exposure conditions. Among these images, the best one was chosen by radiologists and radiological technologists. In the C.R system, the best image of the same patient was acquired with the same method from the F.S system. Both characteristic curves from F.S system and C.R system were analyzed. 3. Results : In the F.S system, the best exposure condition of simple abdomen was 70kVp and 20mAs. In the CR system, with the fixed condition at 70kVp, the image densities of human organs, such as liver, kidney, spleen, psoas muscle, lumbar spine body and iliac crest, were almost same despite different environments (3.2mAs, 8mAs, 12mAs, 16mAs and 20mAs). However, when the exposure conditions were over or under (below) 12mAs, the images between the abdominal wall and the directly exposed part became blurred because the gap of density was decreased. In the C.R system, while the volume of mAs was decreased, an artifact of quantum mottle was increased. 4. Conclusion : This study shows that the exposure condition in the C.R system can be reduced 40% than in the F.S system. This paper concluded that when the exposure conditions are set in CR environment, after the analysis of equipment character, such as image processing system(EDR : Exposure Data Recognition processing), PACS and so on, the high quality of image with maximum information can be acquired with a minimum exposure dose.

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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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3D MDCT Reformation Findings of the Radiographic Contrast Medium Extravasation (조영제 혈관외유출 현상의 3D MDCT 재구성 영상)

  • Kweon Dae-Cheol;Kim Jeong-Koo
    • The Journal of the Korea Contents Association
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    • v.6 no.5
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    • pp.145-152
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    • 2006
  • Radiographic contrast medium may cause tissue injury by extravasation during intravenous automated injection during CT examination. A large - volume extravasation (140 mL) occurred in an adult during contrast-enhanced CT The patient had a swelling and injury on the dorsum right hand of intravenous catheter region. The extravasation injury site was determined by CT scanning. The extavasation compartment syndrome case was examined using four separate display techniques. These 3D MDCT findings might help to determine the best course of treatment for patient with contrast extravasation. 3D image reconstructions provide accurate views of high-resolution and soft-tissue imaging. This paper introduces extravasation with the radiography and 3D MDCT findings.

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Region Detection Using the Feature Point Extraction from Medical Image (의료영상에서 특징점 추출을 이용한 영역추출)

  • 김엄준;성미영
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.429-431
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    • 1998
  • 본 논문에서는 의료 영상 중에서 성대 운동의 불규칙적인 움직임을 판단하여 자동으로 진단 파라미터를 구하는 비디오스트로보키모그래피(Videostrobokymography) 시스템에서 관심 영역을 추출하는 방법을 소개하고자 한다. CCD카메라에 의해 촬영된 영상은 비디오 테이프에 저장된 후 이미지 캡쳐 보드에서 그레이 이미지(gray-level)로 변환되어 저장된다. 입력된 영상은 움직이는 영상을 촬영한 것이므로 관심 영역의 위치가 각 프레임마다 다르다. 또한 실제로 입력된 성대영상들이 점진적인 농도 변화를 보이기 때문에 에지에 의해 영역을 추출하는 일반적인 영역 추출방법은 사용하기 어렵다. 본 논문에서는 두 번의 단계를 통하여 관심 영역을 추출하고 있다. 첫 번째는 입력된 영상에서 노이즈를 제거한 후 각 프레임에서 영상의 최소 에너지를 구한다. 두 번째로 농도 변화 값을 특징 값으로 이용하는 분할-합병 알고리즘(Split-merge Algorithm)을 적용하여 관심 영역을 추출하였다. 제안한 알고리즘을 19명의 성대 영상에 적용하여 분석한 결과 성대의 관심 영역을 추출할 수 있었다. 그리고, 영상의 에너지 값을 이용하는 스네이크 알고리즘(Snake Algorithm)에 적용하여 비교해본 결과 본 연구에서 제안하는 스네이크 알고리즘보다 좋은 성능을 보임을 확인할 수 있었다. 본 연구에서 제안하는 관심 영역 추출 방법은 동적인 변화를 보이는 영상에서 관심 영역을 추출할 수 있을 뿐 아니라 계산 량이 적어 200x280크기의 이미지를 초당 약 40프레임에 대한 관심 영역을 추출할 수 있는 장점이 있다.

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Enhanced latitude for digital projection radiography (디지털 투시촬영의 관용도 향상)

  • Han, Seung-Hoe
    • Korean Journal of Digital Imaging in Medicine
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    • v.5 no.1
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    • pp.98-101
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    • 2002
  • 대조도와 관용도사이의 손실 교환은 투사 방사선 촬영에 있어서 잘 알려져 있고 또한 오랫동안 지속되어온 영상의 질에 있어서의 제약이었다. 전자적인 영상획득의 도입으로 한 영상 내에 넓은 영역의 X-Tay 노출을 포획하는 것이 가능해 졌다. 그러나, 진단에 필요한 세부영역 들을 위해 적절한 대조도를 유지하는 반면, 일반적으로 기대되는 관용도 범위 이외의 정보가 시각화 되어지는 것과 같은 영상의 rendering과 displaying의 문제가 남아 있었다. 이 문서에 묘사되는 EVP(Enhanced Visualization Processing)는 이 문제를 중점적으로 다룬다. 방대한 진단용 CR 영상 데이터베이스로부터 선택된 14개의 검사유형 당 각각 5개의 영상들을 포함한, 총 70개의 영상들을 사용하여 임상 보고서가 제출되었다. 각 영상에 대해, control rendering은 현재 개발되어 있는 automatic tone scaling algorithm(자동 톤 스케일 알고리즘)에 의해 생성되었고, test rendering은 그 control of image에 EVP를 인가함에 의해 생성되었다. 10명의 radiologist들은 각자 개별적으로 140개의 이미지들(70개의 test renderings와 70개의 control renderings)을 9점의 진단 상의 품질 척도로 평가했다. EVP는 세부 대조도의 부당한 손실 없이 증가된 노출 관용도를 제공했다. 많은 영상에서 EVP는 과소 투과 영역에서의 정보의 손실을 줄여주고, 반면 과다 투과 영역의 밝게 빛나는 현상을 실제적으로 감소시켰다. 진단상의 품질 평가는 EVP image와 control image 모두 평균적으로 높았다. 그럼에도 EVP images의 평균 등위는 control image의 그것보다 1 단계 완전히 높은 범위에 있는 것으로 평가되었다. 쌍으로 그 영상들을 보면, EVP images의 76%가 일치하는 control images의 평가 단계보다 1 또는 그 이상 높은 범주인 것으로 평가되었고, 반면 control image의 6% 만이 일치하는 EVP 영상보다 우수한 것으로 평가되었다. 유사한 결과가 연구된 14개의 검사유형에 대해 획득되었다.

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Extracting DEM Using Kompsat Images (Kompsat 영상을 이용한 수치표고모델추출)

  • Choi, Hyun;Kang, In-Joon;Hong, Soon-Heun
    • Journal of Korean Society for Geospatial Information Science
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    • v.10 no.3 s.21
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    • pp.71-77
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    • 2002
  • DEMs(digital elevation models) are generally used to automatically map the channel network and to delineate subbasins. At present, most DEM data are derived from three alternative sources which are ground survey, pphotogrammetric data capture and digitized cartographic data sources. The accuracy of a DEM is dependent on the spatial resolution, quality of the source data, collection and processing procedures, and digitizing systems. weather conditions and nature environment.etc provide us satellite image of the highest quality. However, Match in error of the auto generation DEM was severely affected by physical and environmental conditions at shooting time. This paper shows that real-time operation analysis of applied hydrology after extracting DEM Using a pair of Kompsat images.

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