• 대한전자공학회논문지SP
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• 제48권1호
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• pp.122-131
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• 2011

최근에 널리 사용되고 있는 단일 영상 기반의 3차원 얼굴 복원 방법인 변형 가능한 3차원 얼굴 형상 모델(3D morphable shape model)은 입력 영상으로부터 2차원 얼굴 특징점들을 정확하게 추출할 경우, 입력 얼굴과 유사한 3차원 얼굴 형상을 생성할 수 있다. 그러나 실시간 3차원 얼굴 복원 시스템과 같이 사용자의 협조가 불가능한 경우에는 자동으로 얼굴 특징점들을 추출해야 하기 때문에, 특징점 추출 오류가 발생하여 정확한 3차원 얼굴 형상을 생성하기 어려운 문제가 있다. 이러한 문제를 해결하기 위해서, 본 논문에서는 특징점 추출 시 오추출 특징점과 정추출 특징점을 자동으로 분류하고, 정추출 특징점들만을 이용하여 3차원 얼굴을 복원하는 방법을 제안하였다. 실험결과에서는 특징점 자동 추출 오류를 고려하지 않은 기존 방법과 비교한 결과, 제안방법의 3차원 얼굴 복원 성능이 크게 향상되었음을 확인하였다.

• 대한건축학회연합논문집
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• 제20권6호
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• pp.81-87
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• 2018

In this paper, in order to maximize the input process efficiency of the building energy simulation field, the authors developed the automatic extraction module of spatial information based BIM geometry information. Existing research or software extracts geometry information based on object information, but it can not be used in the field of energy simulation because it is inconsistent with the geometry information of the object constituting the thermal zone of the actual building model. Especially, IFC-based geometry information extraction module is needed to link with other architectural fields from the viewpoint of reuse of building information. The study method is as follows. (1) Grasp the category and attribute information to be extracted for energy simulation and Analyze the IFC structure based on spatial information (2) Design the algorithm for extracting and reprocessing information for energy simulation from IFC file (use programming language Phython) (3) Develop the module that generates a geometry information database based on spatial information using reprocessed information (4) Verify the accuracy of the development module. In this paper, the reprocessed information can be directly used for energy simulation and it can be widely used regardless of the kind of energy simulation software because it is provided in database format. Therefore, it is expected that the energy simulation process efficiency in actual practice can be maximized.

• Spatial Information Research
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• 제18권4호
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• pp.13-22
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• 2010

수질오염의 효율적 관리를 위한 오염총량관리제(TMDL)의 적용에는 하천 수질모델링이 우선 되어야 하며, 이러한 모델링은 하천중심선의 추출이 필수이다. 반면, 현재는 수질모델링을 수행하는 기관들이 제각기 다른 기준으로 하천중심선을 제작하여 정확도가 높지 않으며, 이로 인하여 수질모델링의 수행기관에 따라 통일 유역임에도 수질모델링 결과가 달라지는 문제점이 발생하고 있다. 따라서 본 연구에서는 정확한 하천중심선 추출방법의 개발을 주요 목표로 하였다. 이를 위하여 최대내접원을 활용한 중심선 추출방법을 GIS 기술과 결합하여 자동화 모듈을 개발하였다. 연구 결과 기존 방법의 하천중심선 추출보다 개발된 모듈을 이용한 하천중심선의 추출이 하천형상의 변화를 보다 세부적으로 표출하는 것이 가능하였으며, 정확도 역시 향상되었다. 또한, 기존 방법의 한계점이었던 섬을 포함한 하천의 중심선 추출도 가능하여 보다 정확한 수질모델링의 지원이 가능하였다.

• 산업경영시스템학회지
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• 제44권3호
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• pp.86-97
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• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.

• 대한공간정보학회지
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• 제21권4호
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• pp.45-53
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• 2013

지구 온난화와 이로 인한 해수면의 상승은 명백히 전 지구적으로 일어나고 있는 변화이며 해안선의 변화 또한 동반되고 있다. 해안선은 해수면의 상승뿐만 아니라 인위적인 활동에 의해서도 변화할 수 있으나 지구온난화에 의한 해안선 변화의 파악은 지구 온난화의 진행을 파악할 수 있는 지표로써 활용이 가능하다. 따라서 본 연구의 목적은 자동으로 해안선을 추출 및 변화를 파악하는 데에 있다. 본 연구에서는 자동으로 해안선을 추출하기 위해서 수분지수를 활용하여 물과 육지의 대조를 극대화하였으며, 해안선의 자동 추출이 용이하도록 하였다. 수분지수로 변환된 영상에서 자동으로 물과 육지를 분할하기 위하여 적정 임계값을 자동으로 찾을 수 있도록 영상처리 기법을 적용하였고, 경계선 검출 알고리즘을 통하여 해안선을 추출하였으며 추출된 해안선으로 변화를 탐지하는 방법론을 제시하고자 하였다. 자동으로 물과 육지를 분할하고 경계선을 찾는 영상처리 기법은 다른 자료의 도움 없이 LANDSAT 영상만을 이용하여 적용될 수 있으며 추출된 해안선 또한 기준자료로 이용된 NLCD(National Land Cover Database) 자료와의 비교를 통해 유사하다는 것을 확인할 수 있었다. 또한 지구 온난화의 지표로써의 활용 가치를 확인하기 위해 연구 대상지역을 지층의 온도가 연중 $0^{\circ}C$ 이하로 항상 얼어 있는 영구동토로 선정하여 영구동토의 해빙으로 인한 해안선 변화를 정량적으로 확인할 수 있었으며 해안선의 변화가 가속화한다는 사실을 확인할 수 있었다.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.599-613
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• 2022

Non-proliferative diabetic retinopathy is a representative complication of diabetic patients and is known to be a major cause of impaired vision and blindness. There has been ongoing research on automatic detection of diabetic retinopathy, however, there is also a growing need for research on an automatic severity classification system. This study proposes an automatic detection system for pathological symptoms of diabetic retinopathy such as microaneurysms, retinal hemorrhage, and hard exudate by applying the Faster R-CNN technique. An automatic severity classification system was devised by training and testing a Random Forest classifier based on the data obtained through preprocessing of detected features. An experiment of classifying 228 test fundus images with the proposed classification system showed 97.8% accuracy.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.245-245
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• 2005

This paper addresses the use of directional textural information for connecting road segments. In urban scene, some roads are occluded by buildings, casting shadow of buildings, trees, and cars on streets. Automatic extraction of road network from remotely sensed high resolution imagery is generally hindered by them. The results of automatic road network extraction will be incomplete. To overcome this problem, several perceptual grouping algorithms are often used based on similarity, proximity, continuation, and symmetry. Roads have directions and are connected to adjacent roads with certain angles. The directional information is used to guide road fragments connection based on roads directional inertia or characteristics of road junctions. In the primitive stage, roads are extracted with textural and direction information automatically with certain length of linearity. The primitive road fragments are connected based on the directional information to improve the road network. Experimental results show some contribution of this approach for completing road network, specifically in urban area.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.35-38
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• 2003

In this paper, I propose an automatic background extraction method and continuous background updating technique. Because there is a movement of a vehicle and a change of a background is feeble, the area moving through the time axis is looked for and a background and a vehicle image is divided. A way to give dynamically the threshold which divides the image frame into a vehicle image and the background in a space is enforced. Through the repetition of the above-mentioned process, the background pictorial image is gained. Using the karlman filter technique, the update is done so that a background image can obey a climate situation and an environmental change in day and night. A background image processed algorithm is better than the existent one. Through simulation, the feasibility of the algorithm has been verified.

• 전자공학회논문지D
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• 제34D권7호
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• pp.88-96
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• 1997

As the need of automatized system has been increased recently together with the development of industrial and military technologies, the adaptive real-time target detection technologies that can be embedded on vehicles, planes, ships, robots and so on, are hgihly demanded. Accordingly, this paper proposes a novel approach to detect and segment the moving targets using the binary phase extraction joint transform correlator (BPEJTC), the advanced image subtraction filter and convex hull processing. The BPEJTC which was used as a target detection unit mainly for target tracking compensating the camera movement. The target region has been detected by processing the successful three frames using the advanced image subtraction filter, and has become more accurate by applying the developed convex hull filter. As shown by some experimental results, it is expected that the proposed approaches for compensation of the camera movement and segmentationof of target region, can be used for th emissile guiddance, aero surveillance, automatic inspectin system as well as the target detection unit of automatic target recognition system that request adaptive real-time processing.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.525-528
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• 2009

Recently, image classification has been an important task in various fields. Generally, the performance of image classification is not good without the adjustment of image features. Therefore, it is desired that the way of automatic feature extraction. In this paper, we propose an image classification method which adjusts image features automatically. We assume that texture features are useful in image classification tasks because natural images are composed of several types of texture. Thus, the classification accuracy rate is improved by using distribution of texture features. We obtain texture features by calculating image features from a current considering pixel and its neighborhood pixels. And we calculate image features from distribution of textures feature. Those image features are adjusted to image classification tasks using Genetic Algorithm. We apply proposed method to classifying images into "head" or "non-head" and "male" or "female".