• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제11권11호
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• pp.411-418
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• 2022

최근 항만에서는 부정확한 컨테이너 적재로 인해 컨테이너가 강풍에 쉽게 쓰러지는 컨테이너 붕괴 사고가 빈번이 발생하고 있으며 이는 물적 피해와 항만 시스템 마비로 이어지고 있다. 본 논문에서는 이런 사고를 미연에 방지하기 위해 딥러닝 기반 컨테이너 적재 상태 및 사고 위험도 검출 시스템을 제안한다. 제안된 시스템은 darknet 기반 YOLO 모델을 활용하여 컨테이너 상하의 코너캐스팅을 통해 컨테이너 정렬 상태를 실시간으로 파악하고 관리자에게 사고 위험도를 알리는 시스템이다. 제안된 시스템은 추론 속도, 분류 정확도, 검출 정확도 등을 성능 지표와 실제 구현 환경에서 최적의 성능을 보인 YOLOv4 모델을 객체 인식 알고리즘 모델로 선택하였다. 제안된 알고리즘인 YOLOv4가 YOLOv3보다 추론속도와 FPS의 성능 측면에서 낮은 성능을 보이기는 했지만, 분류 정확도와 검출 정확도에서 강력한 성능을 보임을 증명하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.3086-3103
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• 2017

Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.

• 한국자동차공학회논문집
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• 제16권2호
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• pp.66-73
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• 2008

In this paper, ultrasonic range system which detects parking lot in parking area is studied. The important part for detecting parking lot accurately is to detect the first and second corners of possible parking lot, and for that, new method using multiple echo function is introduced in this paper. Many probabilistic methods have been used to reduce uncertainties of ultrasonic sensor for distance and location of objects. Method using multiple echo, however, gives accurates results as well as simple algorithm. For experiments in parking space, ultrasonic range system was attached to a Pioneer AT-2 and final parking space map was created in a fusion with position information from wheels of a Pioneer AT-2. We will show the results are compared with error of another methods.

• 한국산학기술학회논문지
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• 제15권12호
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• pp.7302-7308
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• 2014

특정한 제한을 두지 않는 복잡한 자연환경에서 사용자가 원하는 목표 물체만을 정확하게 검출하는 작업은 컴퓨터 비전 및 영상처리 분야에서 중요하지만 매우 어려운 문제 중의 하나이다. 본 논문에서는 반사가 존재하는 여러 환경에서 목표하는 물체를 강인하게 검출하는 새로운 방법을 제안한다. 제안된 방법에서는 먼저 스테레오 카메라를 이용하여 목표 물체를 촬영한 다음, 물체를 가장 잘 표현하는 라인과 코너 특징들을 추출한다. 그런 다음, 촬영된 좌우 영상으로부터 호모그래픽 변환을 이용하여 실제로 존재하지 않는 반사된 특징들을 효과적으로 제거한다. 마지막으로, 반사된 특징들을 제거한 실제 특징들만을 군집화하여 대상 물체만을 강건하게 검출한다. 본 논문의 실험결과에서는 제안된 알고리즘이 기존의 알고리즘에 비해서 반사가 존재하는 자연 환경에서 목표 물체를 보다 강인하게 검출한다는 것을 보여준다.

• 전기전자학회논문지
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• 제18권4호
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• pp.536-543
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• 2014

Terrain classification is still a challenging issue in image processing, especially with high resolution satellite images. The well-known obstacles include low accuracy in the detection of targets, especially for the case of man-made structures, such as buildings and roads. In this paper, we present an efficient approach to classify and detect building footprints, foliage, grass and road from high resolution grayscale satellite images. Our contribution is to build a strong classifier using AdaBoost based on a combination of co-occurrence and Haar-like features. We expect that the inclusion of Harr-like feature improves the classification performance of the man-made structures, since Haar-like feature is extracted from corner features and rectangle features. Also, the AdaBoost algorithm selects only critical features and generates an extremely efficient classifier. Experimental result indicates that the classification accuracy of AdaBoost classifier is much higher than that of the conventional classifier using back propagation algorithm. Also, the inclusion of Harr-like feature significantly improves the classification accuracy. The accuracy of the proposed method is 98.4% for the target detection and 92.8% for the classification on high resolution satellite images.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1499-1502
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• 2002

A method for acquiring an environmental map by integrating distance data obtained by sonars of a moving robot with web interface is proposed. Sonar data contains outliers in some cases such as ultrasonic beam is projected onto a corner of an object. Therefore, the influence of the outliers should be reduced by detecting outliers. In our method, the outliers are detected by two ways: (i) a method considering geometrical .elation among the observed surface and the projected ultrasonic beau, and (ii) a method considering consistency with data obtained by other sonars. By measurement by the sonar, the distance from the sonar to the obstacle is obtained. Assuming the two dimensional space we can know that the inside of the sector, whose renter coincide with the sonar and whose radius is equal to the obtained distance, is the free area, and a part of the arc of this sector is the obstacle area. The generation of the environmental map is done by integrating the free area and the obstacle area obtained by each measurement by the sonars. Before the integration, the outliers detection is done by two ways mentioned above. Experimental results show that obtained maps obtained by our methods with outliers defection are much better than those by a method without outliers detection.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.558-565
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• 2013

The process and efficiency of monitoring building and construction violations is a concern of the construction industry. The detection of violations requires appropriate and sufficiently accurate spatial information to manage and support a comprehensive inspection process and monitor compliance. A building inspection workflow must extract appropriate spatial and measurement in-formation from a variety of sources, identify potential violations across a range of compliance criteria and determine the quality of resulting inspection reports. This paper presents a framework for supporting building inspections using spatial information and methods to detect construction violations and compliance. Current inspection processes involve issues around the identification of building violations, access to building regulations and existing spatial information, integration of a range of spatial and non-spatial information, and the quality of decisions within the inspection workflows. A survey of building inspectors was conducted and used together with the issues identified to establish the requirements for a spatial inspection framework. The results demonstrate how such a framework can support improved decision-making and reduced fieldwork effort in detecting and measuring the accuracy of building violations involving building placements, street offsets and footprint areas.

• 전기전자학회논문지
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• 제10권1호
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• pp.40-48
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• 2006

본 논문에서는 3차원 선소로부터 건물의 rooftop 평면을 추정하는 새로운 기법이 제안되었다. 3차원 rooftop 평면 추정은 3차원 선소의 계층적 grouping에 기반한 것으로, 끊어진 3차원 선소의 병합으로부터 시작된다. 병합된 3차원 선소는 평면 추정기법에 의해 rooftop 검출에 적용되는데, 평면 추정을 위해 T자형 모서리 및 L자형 모서리 검출을 통해서 신뢰성 있는 접속점이 구해진다. 구해진 접속점에 의해 가정된 rooftop 평면이 발생될 수 있으며, 건물 평면의 속성에 의해 최종적으로 검증되어, 건물의 rooftop 모델이 결정된다. Avenches 항공영상 데이터로부터 구해진 모의영상에 의해 실험이 수행되었는데, 실험 결과 0.4 - 1.3 meter의 오차를 가진 rooftop 평면 모델이 구해졌으며, 이는 종래의 영역기반 스테레오에 의해 구해진 고도에 비해 정확도가 2.5배 정도 향상되었음을 알 수 있었다.

• 전자공학회논문지CI
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• 제47권1호
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• pp.160-170
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• 2010

본 논문은 Haar 웨이브릿변환과 평균 박스필터에 기반을 둔 Haar 웨이브릿 특징 검출자를 제안한다. 원 영상을 Haar 웨이브릿 변환을 통해 분해하여 영상의 분산정보를 얻고 영상 식별을 위한 특징정보를 추출한다. 영역을 나타내는 주위영역들 중에 분산이 가장 큰 영역의 관심점을 검출하기 위하여 국부 분산정보를 비교하는 평균 박스필터를 적용하고 빠른 계산을 위한 적분영상 기법을 사용한다. Haar 웨이브릿 변환과 평균 박스필터를 이용하여 제안한 검출자는 밝기 변화, 스케일 변화, 영상의 회전에 민감하지 않는 특성을 제공할 수 있다. 실험결과는 제안한 방법이 적은 관심점을 사용하는 경우에도 기존의 DoG 검출자와 Harris corner 검출자에 비해 더 높은 repeatability와 효율성 그리고 매칭정확성을 달성할 수 있음을 보여준다.

• 한국정밀공학회지
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• 제24권9호
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• pp.148-157
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• 2007

A new method which uses distance fields scheme and marching cube algorithm is proposed in order to get an accurate offset model of arbitrary shapes composed of triangular net. In the method, the space bounding the triangular net is divided into smaller cells. For the efficient calculation of distance fields, valid cells which will generate a portion of offset model are selected previously by the suggested detection algorithm. These valid cells are divided again into much smaller voxels which assure required accuracy. At each voxel distance fields are created by calculating the minimum distances between corner points of voxels and triangular net. After generating the whole distance fields, the offset surface were constructed by using the conventional marching cube algorithm together with mesh smoothing scheme. The effectiveness and validity of this new offset method was demonstrated by performing numerical experiments for the various types of triangular net.