• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.703-706
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• 2004

나선형 CT 혈관촬영에서 획득한 영상의 분석를 통해서 폐색전증이 의심되는 부위를 자동으로 검출하는 방법으로, 연구 대상은 20명의 환자를 대상으로 분석하였으며 CT 검사 후 방사선과 의사가 정상소견을 받은 환자 5명과 폐색전증이 있는 판독소견을 가진 15명을 대상으로 비교 분석하였다. CT 검사하는 동안에 조영제를 투입하면, 폐색전증이 발생한 부위는 조영제 양과 분포가 불균등하여 명암값이 낮게 검출된다. 검출방법으로는 전처리 작업으로 폐영역만을 분할하고, 분할된 폐영역에서 혈관을 찾기 위해 모폴로지기법를 적용하여 세선화(thinning) 작업을 진행한다. 다음 공정으로는 경계선을 찾아 local watershed를 적용하여 혈관을 검출하고, 검출된 혈관내에서 원형모델을 적용하여 모폴로지(morphology)을 통해 국소 부위의 미세한 농도변화를 인지하여 색전이 발생한 영역을 자동검출하였다. 본 논문의 자동검출시스템에서는 색전증이 있는 경우에 true positive의 발생빈도는 case 당 4.5개가 검출되었다. 정상인의 경우에도 혈류의 흐름, 혈류의 분기점, 노이즈로 인한 false positive의 빈도는 case 당 2.6개가 발생하여 전체적으로 false positive는 5.2개가 검출되었다. 본 논문은 false positive의 비율이 높게 검출되었지만 폐영역 CT 검사의 컴퓨터지원진단시스템(computer aided diagnosis)의 향후 연구과제에 방향을 제시할 수 있을 것이라 사료된다.

• Journal of IKEEE
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• v.28 no.1
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• pp.65-71
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• 2024

This paper proposes a neural network that can reduce the number of parameters while reducing matching errors in occluded regions to increase the accuracy of depth maps in stereo matching. Stereo matching-based object recognition is utilized in many fields to more accurately recognize situations using images. When there are many objects in a complex image, an occluded area is generated due to overlap between objects and occlusion by background, thereby lowering the accuracy of the depth map. To solve this problem, existing research methods that create context information and combine it with the cost volume or RoIselect in the occluded area increase the complexity of neural networks, making it difficult to learn and expensive to implement. In this paper, we create a depthwise seperable neural network that enhances regional feature extraction before cost volume generation, reducing the number of parameters and proposing a neural network that is robust to occlusion errors. Compared to PSMNet, the proposed neural network reduced the number of parameters by 30%, improving 5.3% in color error and 3.6% in test loss.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.1-4
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• 2016

효율적으로 깊이지도를 획득하기 위해 다양한 방법의 지역 기반스테레오 매칭 방법이 사용된다. 일반적인 지역기반 스테레오 매칭에 사용되는 비용값 계산 방법을 통해 깊이지도를 생성하게 되면 객체의 경계 영역이 무너지거나, 유사한 텍스쳐 정보가 연속적으로 나타나는 영역에서 부정확한 깊이값을 얻는 문제가 발생한다. 본 논문에서는 깊이지도의 정확성을 높이기 위해 2가지 단계를 거쳐 최종 깊이지도를 생성한다. 처음으로, 일반적으로 사용하는 지역기반 스테레오 매칭 비용 함수와 입력 영상의 기울기를 고려한 초기 비용값을 가이드 필터를 이용하여 최적의 비용값을 찾아 초기 변위지도를 생성한다. 스테레오매칭을 수행할 경우, 시점의 차이로 인해 보이지 않는 영역에서 정확한 변위값을 찾지 못하는 문제가 발생한다. 이러한 문제를 해결하기 위해 좌영상과 우영상을 기반으로 획득한 변위지도를 사용하여 교차검사를 함으로써 폐색영역을 찾아낸다. 폐색 영역을 이웃한 화소의 값을 사용하여 채울 경우 실선과 같은 오류가 결과 영상에 나타나게 된다. 이러한 오류 영역을 제거하기 위해 마지막으로 가중치를 적용한 중간값 필터를 적용한다. 실험 결과 제안한 방법을 사용하여 획득한 깊이지도가 기존의 방법보다 정확한 깊이값을 얻는 것을 확인할 수 있었다.

• Spatial Information Research
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• v.19 no.1
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• pp.51-59
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• 2011

We produced true ortho images after interpolating occlusion areas and relief displacement of building as well as producing ortho-images to use backward image of ADS which is a aerial digital camera of line type. Also, I was able to produce high quality ortho-images using a small mount of Ground Control Points(GCP) relatively to compare to frame type camera from the evaluation of horizontal position accuracy using ground check points, photo control points for the verification of ortho-images and true-ortho images. Also, I was able to verify the effectiveness in interpolating occlusion areas cause the length overlap was 100% when producing true-ortho images of line type camera.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.216-224
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• 1997

In this paper, we propose a depth information extraction method for intermediate image synthesis. As stereo matching method, MBS(Multiple-Baseline Stereo) method has been proposed, in which the matching accuracy increases by using the multiple camera, but there are some inherent problems such as computational complexity, boundary overreach(BO) in depth map, and occlusion. So, we propose the modified version of MBS so called Multi-Resolution MBS(MR-MBS). Moreover, we also propose an adaptive occlusion area processing technique to improve the accuracy of the depth information in occlusion area.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.1-9
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• 2008

In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.415-425
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• 2007

In this study, we generated an orthophoto with both LIDAR data and aerial images and compared it with that generated from only the images. For the accuracy assessment of these orthophotos, we performed not only qualitative analysis based on visual inspection but also quantitative analysis by measuring horizontal inconsistency, boundary coordinates and similarity measures on buildings. Based on the visual inspection and horizontal inconsistency, the orthophoto based on LIDAR DSM appeared to be more closer to a true-orthophoto. However, the analysis on measurements of boundary coordinates and similarity measures indicates that the orthophoto based on LIDAR DSM is more vulnerable to double mapping on occluded areas. Accordingly, if we apply an effective solution on double mapping or use only the central areas of the aerial images where occluded areas are rarely founded, we can generate automatically true-orthophotos based on a LIDAR DSM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.77-83
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• 2020

The technologies of 3D spatial information, such as Smart City and Digital Twins, are developing rapidly for managing land and solving urban problems scientifically. In this construction of 3D spatial information, an object using aerial photo images is built as a digital DB. Realistically, the task of extracting a texturing image, which is an actual image of the object wall, and attaching an image to the object wall are important. On the other hand, occluded areas occur in the texturing image. In this study, the ResNet algorithm in deep learning technologies was tested to solve these problems. A dataset was constructed, and the street tree was detected using the ResNet algorithm. The ability of the ResNet algorithm to detect the street tree was dependent on the brightness of the image. The ResNet algorithm can detect the street tree in an image with side and inclination angles.

• Journal of Drive and Control
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• v.19 no.3
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• pp.9-15
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• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

• Journal of Energy Engineering
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• v.21 no.3
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• pp.237-242
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• 2012

This study presents numerical solutions of the two-dimensional Navier-Stokes equations for supersonic unsteady flow in a convergent-divergent nozzle with a isolator. The TVD scheme in generalized coordinates is employed in order to calculate the moving shock waves caused by thermal choking. We discuss on transient characteristics, unstart phenomena, fluctuations of specific thrust caused by thermal choking and effects of isolator. The adverse pressure gradient caused by heat addition brings about separation of the wall boundary layers and formation of the oblique shock wave that proceed to upstream. The proceeding speed of the oblique shock wave to upstream direction for the convergent-divergent nozzle with isolator is lower than that for the nozzle without isolator.