• 제어로봇시스템학회논문지
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• 제3권1호
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• pp.32-39
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• 1997

One of the most important performance criteria in tuning the gain of position loop controller for CNC machining center is the contour error. In this papre we analyze contour error in the linear and circular interpolations for the axis-matched and mismatched cases. To have small contour errors, it is necessary to set the P gain for each axis to be same. And the D gain should be much smaller than the P gain. Baded on the analysis in the frequency domain, we propose a gain tuning method for the P and PD controllers. We show that the PD controller is better than the P controller. The effectiveness of this method is demonstrated by experiments.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.333-336
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• 2007

We propose a simple method for tracking a nonparameterized subject contour in a single video stream with a moving camera and changing background. Then we present a method to eliminate the tracked contour object by replacing with the background scene we get from other frame. Our method consists of two parts: first we track the object using LOD (Level-of-Detail) canny edge maps, then we generate background of each image frame and replace the tracked object in a scene by a background image from other frame that is not occluded by the tracked object. Our tracking method is based on level-of-detail (LOD) modified Canny edge maps and graph-based routing operations on the LOD maps. To reduce side-effects because of irrelevant edges, we start our basic tracking by using strong Canny edges generated from large image intensity gradients of an input image. We get more edge pixels along LOD hierarchy. LOD Canny edge pixels become nodes in routing, and LOD values of adjacent edge pixels determine routing costs between the nodes. We find the best route to follow Canny edge pixels favoring stronger Canny edge pixels. Our accurate tracking is based on reducing effects from irrelevant edges by selecting the stronger edge pixels, thereby relying on the current frame edge pixel as much as possible. This approach is based on computing camera motion. Our experimental results show that our method works nice for moderate camera movement with small object shape changes.

• 한국항공우주학회지
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• 제43권10호
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• pp.902-909
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• 2015

본 논문에서는 인공위성 근접운용을 위한 단일 영상 기반 상대항법에 대한 연구를 수행하였다. 추적 위성은 하나의 카메라 센서만을 이용하여 표적 위성을 관측하고 영상추적을 통해 표적 위성의 위치 정보를 얻게 된다. 그러나 단일 영상만을 이용할 경우, 표적과의 상대 거리에 해당하는 깊이 정보를 얻기 힘들다. 이러한 문제를 해결하기 위해 능동 윤곽 기법을 영상 추적에 적용하였다. 능동 윤곽 기법을 통해 표적의 이미지 크기를 얻을 수 있고 이러한 형상 정보를 바탕으로 상대 거리를 간접적으로 계산할 수 있다. 두 인공 위성이 상대 운동을 하는 우주환경을 구현하고 가상의 카메라 영상을 생성하기 위해 3차원 가상현실이 이용되었다. 추적 위성은 UKF를 이용하여 표적 위성에 대한 상대위치를 추정하면서 글라이드슬로프 접근 기법을 이용하여 표적 위성에 근접한다. 상대항법의 성능을 분석하기 위해서 폐 루프 시뮬레이션을 수행하였다.

• 대한기계학회논문집
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• 제19권5호
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• pp.1220-1228
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• 1995

In this paper, we consider the problems of tracking an object in a real image. In evaluating these problems, we explore a new technique based on an active contour model commonly called a snake model, and propose the active bar models to represent target. Using this model, we simplified the target welection problems, reduced the search space of energy surface, and obtained the better performances than those of snake model. This approach improves the numerical stability and the tendency for points to bunch up and speed up the computational efficiency. Representing the object by active bar, we can easily obtain the zeroth, the first, and the second moment and it facilitates the target tracking. Finally, we present the good result for the visual tracking problem.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.277-280
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• 2007

특정컬러정보 검출기반의 이동객체 탐색 알고리듬을 구현한다. 입력 이미지에 대해 조도변화 및 노이즈 제거 등을 위해 전처리 과정을 거치고, 이동객체 탐색은 R,G,B 각 채널의 영상차를 이용하여 객체를 검색한다. 실험 결과 검색 속도는 윤관선 탐색 및 정합법에 비해 15% 향상되었고 안정적이다. 또한 컬러 정보 기반의 객체 탐색이 가능함을 제시하였다.

• 대한전기학회논문지
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• 제38권3호
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• pp.209-216
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• 1989

A method for extracting the elemental information for an efficient representation of the boundary of industrial parts, from the contours of the mechanical parts, is presented. We have analyzed the performance of the boundary representation using lines and circles. We have also analyzed and compared the performance of the proposed method with that of CW tracking-RL searching method. The result of the analysis has shown that the method suggested in this paper is twice faster than CW tracking-RL searching method. The same result could also be observed in experiments.

• 한국정밀공학회지
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• 제15권10호
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• pp.180-192
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• 1998

This paper introduces a new self-organizing fuzzy logic controller (SOFLC) for precision contour machining in the presence of large disturbances which adjusts both input and output membership functions simultaneously. The parameters of the proposed controller are self-tuned in real-time according to a continuous measurement of the performance of the controller itself and estimated disturbance values. The proposed controller as well as a conventional fuzzy logic controller and a PID controller were simulated and implemented on a 3-axis milling machine in contour milling. Both the simulations and experiments show that the self-organizing fuzzy logic controller has superior performance in terms of contour tracking accuracy compared with the other two controllers.

• 한국공작기계학회논문집
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• 제14권6호
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• pp.1-7
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• 2005

This paper deals with the position control for a feed drive system in CNC milling machine. The study shows that reduction in tacking error does not necessarily increase contouring accuracy, and proposes that a proper control scheme is able to exhibit the optimal tracking and contouring accuracy. The proposed scheme is to fix the parameter of the contouring control, and to find the optimal value of the parameter of the tracking control, which is automatically tuned. The effectiveness of the proposed scheme is confirmed through simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.740-745
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• 2003

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.474-479
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• 2003

In this paper, we proposed the novel method for the recognition of English calling cards by using the projection method and the enhanced RBF (Radial Basis Function) network. The recognition of calling cards consists of the extraction phase of character areas and the recognition phase of extracted characters. In the extraction phase, first of all, noises are removed from the images of calling cards, and the feature areas including character strings are separated from the calling card images by using the horizontal smearing method and the 8-directional contour tracking method. And using the image projection method, the feature areas are split into the areas of individual characters. We also proposed the enhanced RBF network that organizes the middle layer effectively by using the enhanced ART1 neural network adjusting the vigilance threshold dynamically according to the homogeneity between patterns. In the recognition phase, the proposed neural network is applied to recognize individual characters. Our experiment result showed that the proposed recognition algorithm has higher success rate of recognition and faster learning time than the existing neural network based recognition.