• 대한의용생체공학회:의공학회지
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• 제20권1호
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• pp.69-73
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• 1999

본 논문에서는 자기공명영상의 외부윤곽을 검출하기 위한 Snakes에 근거한 알고리즘을 제안하였다. 첫 번째 자기공명영상에서 물체의 외부윤곽을 수동으로 검출하고, 이를 다음 자기공명영상의 외부윤곽을 검출하기 위한 초기 제어점으로 사용하였다. 나머지 자기공명영상의 외부윤곽을 자동으로 검출하기 위하여 이웃한 영상간의 상관성을 이용한 에너지항을 Greedy Snakes알고리즘에 추가하였다. 제안한 알고리즘의 정확도를 평가하기 위해 BMD 측정방법을 사용하였으며, 제안된 알고리즘의 결과가 Greedy 알고리즘의 결과에 비해 높은 BMD 값을 얻음으로써 수동검출한 외부윤곽과 더욱 유사한 결과를 구할 수 있었다.

• 한국가스학회지
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• 제4권1호
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• pp.1-8
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• 2000

매설되어 있는 배관에 위험성을 초래하는 요소중 하나는 굴삭기와 천공기 같은 타공사에 의한 것이다. 타공사에 의한 피해는 다른 원인에 의한 것보다 사고발생시 막대한 인명피해를 초래하기 때문에 안전관리가 매우 필요하다. 따라서 본 연구에서는 타공사를 조기에 감시하기 위해서 진동센서를 이용하여 타공사와 같은 충격신호를 감지할 수 있는 지와 얼마만큼 떨어진 거리까지 전파할 수 있는지에 대하여 한국가스공사 배관에 적용하여 실험하였다. 그리고 감지된 신호의 충격위치를 알아보기 위하여 모의배관내에서의 실험을 수행하였다. 그 결과 가까운 거리에서 감지된 충격신호는 주된 신호가 고주파수 대역이며, 거리가 멀어질수록 고주파수 대역의 성분들은 소멸되어지고 저주파수 대역만이 남아 있게 된다. 또한 5.3km 떨어진 공급관리소에서의 실험을 통하여 40kg의 물체가 l0cm, 5cm의 높이에서 자유낙하 하였을 때 진동센서(가속도계)를 통하여 감지 가능함을 확인하였다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.451-454
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• 2007

There is an inseparable relation between human race and engineering work. As world developed into highly industrialized society, a diversity of large structures is being built up correspondently to limited topographical circumstance. Though large structures are national establishments which provide us with convenience of life, there are some disastrous possibilities which were never predicted such as ground subsidence and degradation. It is very difficult to analyze the volume of total metamorphosis with the relative displacement measurement system which is now used and it is impossible to know whether there is structural metamorphosis within a permissible range of design or not. In this research with an object of 13-year-old earthen dam, through generating point-cloud which has 3D spatial coordinates(x, y, z) of this dam by means of 3D Laser Scanning, we can get real configuration data of slanting surface of this dam with this method of getting a number of 3D spatial coordinates(x, y, z). It gives 3D spatial model to us and we can get various information of this dam such as the distance of slanting surface of dam, dimensions and cubic volume. It can be made full use of as important source material of reinforcement and maintenance works to detect previously the bulging of the dam through this research.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.113-115
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• 2005

This thesis presents a method for 3D modeling of facial expression from frontal and mirror-reflected multi-image. Since the proposed system uses only one camera, two mirrors, and simple mirror's property, it is robust, accurate and inexpensive. In addition, we can avoid the problem of synchronization between data among different cameras. Mirrors located near one's cheeks can reflect the side views of markers on one's face. To optimize our system, we must select feature points of face intimately associated with human's emotions. Therefore we refer to the FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) defined by MPEG-4 SNHC (Synlhetic/Natural Hybrid Coding). We put colorful dot markers on selected feature points of face to detect movement of facial deformation when subject makes variety expressions. Before computing the 3D coordinates of extracted facial feature points, we properly grouped these points according to relative part. This makes our matching process automatically. We experiment on about twenty koreans the subject of our experiment in their late twenties and early thirties. Finally, we verify the performance of the proposed method tv simulating an animation of 3D facial expression.

• 대한임베디드공학회논문지
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• 제18권5호
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• pp.203-208
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• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.

• 로봇학회논문지
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• 제17권3호
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• pp.255-263
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• 2022

3D object detection pipelines often incorporate RGB-based object detection methods such as YOLO, which detects the object classes and bounding boxes from the RGB image. However, in complex environments where objects are heavily cluttered, bounding box approaches may show degraded performance due to the overlapping bounding boxes. Mask based methods such as Mask R-CNN can handle such situation better thanks to their detailed object masks, but they require much longer time for data preparation compared to bounding box-based approaches. In this paper, we present a 3D object recognition pipeline which uses either the YOLO or Mask R-CNN real-time object detection algorithm, K-nearest clustering algorithm, mask reduction algorithm and finally Principal Component Analysis (PCA) alg orithm to efficiently detect 3D poses of objects in a complex environment. Furthermore, we also present an improved YOLO based 3D object detection algorithm that uses a prioritized heightmap clustering algorithm to handle overlapping bounding boxes. The suggested algorithms have successfully been used at the Artificial-Intelligence Robot Challenge (ARC) 2021 competition with excellent results.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.77-80
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• 2022

Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. It has been populated because of the accuracy and consistency in terms of QC (Quality Control) of inspection processes. Also, it is important to predict the performance of an AVI to meet customer's specification in advance. AVI are usually suffered from false negative and positives. It can be overcome by providing extra information such as 3D depth information. Stereo vision processing has been popular for depth extraction of the 3D images from 2D images. However, stereo vision methods usually take long time to process. In this paper, retro optical system using reflectors is proposed and experimented to overcome the problem. The optical system extracts the depth without special SW processes. The vision sensor and optical components such as illumination and depth detecting module are integrated as a unit. The depth information can be extracted on real-time basis and utilized and can improve the performance of an AVI system.

• 한국정밀공학회지
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• 제30권6호
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• pp.601-606
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• 2013

3D scanning is a technique to measure the 3D shape information of the object. Shape information obtained by 3D scanning is expressed either as point cloud or as polygon mesh type data that can be widely used in various areas such as reverse engineering and quality inspection. 3D scanning should be performed as accurate as possible since the scanned data is highly required to detect the features on an object in order to scan the shape of the object more precisely. In this study, we propose the method on finding the location of feature more accurately, based on the extended Biplane SNAKE with global optimization. In each iteration, we project the feature lines obtained by the extended Biplane SNAKE into each image plane and move the feature lines to the features on each image. We have applied this approach to real models to verify the proposed optimization algorithm.

• 대한원격탐사학회지
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• 제21권3호
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.