• 한국생산제조학회지
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• 제20권4호
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• pp.386-394
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• 2011

This paper is concerned with the application of the vision control scheme for robot's point placement task in discontinuous trajectory caused by obstacle. The proposed vision control scheme consists of four models, which are the robot's kinematic model, vision system model, 6-parameters estimation model, and robot's joint angles estimation model. For this study, the discontinuous trajectory by obstacle is divided into two obstacle regions. Each obstacle region consists of 3 cases, according to the variation of number of cameras that can not acquire the vision data. Then, the effects of number of cameras on the proposed robot's vision control scheme are investigated in each obstacle region. Finally, the practicality of the proposed robot's vision control scheme is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 하계학술대회
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• pp.262-265
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• 2012

In this paper we propose a new deinterlacing method with block classification and motion vector smoothing. The proposed method classifies a block, then depending on the region it belongs to, the motion estimation or line averaging is applied. To classify a block its variance is calculated. Then, for those blocks that belong to simple non-texture region the line averaging is done while motion estimation is applied to complex region. The motion vector field is smoothed using median filter what yields more accurate interpolation. In the experiments for the subjective evaluation, the proposed method bas shown satisfying results in terms of computation time consumption and peak signal-to-noise ratio. Due to the simplicity of the algorithm computation time was drastically decreased.

• 제어로봇시스템학회논문지
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• 제21권8호
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• pp.773-780
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• 2015

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2006년도 춘계종합학술대회
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• pp.397-401
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• 2006

In this paper, we proposed a high precision location estimation algorithm using an enhanced decision scheme for RTLS and analyzed its performance in point of an average estimation error distance at 2D coordinates searching area, $300m\times300m$ and LOS propagation environments. Also the performance was compared with that of conventional TDOA algorithm according to the number of available reader and received sub-blink. From the results, we confirmed that the proposed location estimation algorithm using an enhanced decision scheme was able to improve an estimation accuracy even in boundary region of searching area. Moreover, effectively reduced an error distance in entire searching area so that increased the stability of location estimation in RTLS. Therefore, we verified that the proposed algorithm provided a more higher estimation accuracy and stability than conventional TDOA.

• 디지털산업정보학회논문지
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• 제8권4호
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.240-251
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• 2016

This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

• 한국멀티미디어학회논문지
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• 제6권7호
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• pp.1121-1130
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• 2003

본 논문에서는 움직임의 시간적 연속성을 이용한 새로운 움직임 추정 알고리듬을 제안한다. 기존의 전역 탐색 방법 (FSA)에서와 같이 전역 탐색 영역 (GSR)을 정하고, GSR 안에 시간적으로 인접한 블록들의 움직임 벡터들로 예측한 국부 탐색 영역 (LSR)들을 정한다. 여기서 시간적으로 인접한 블록은 이전 프레임의 블록 중 움직임 벡터로 볼 때 현재 프레임에 영향을 끼칠 가능성이 있는 블록이다. 그리고 이 LSR들로 만든 영역에 대해서만 움직임 탐색을 행한다. 모의 실험 결과, 제안한 방법은 기존의 FSA 방법에 비해 탐색 영역을 줄여 계산량을 현저히 낮추면서도 우수한 화질을 유지하는 것을 볼 수 있었다.

• 한국멀티미디어학회논문지
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• 제7권8호
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• pp.1025-1034
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• 2004

본 논문에서는 움직임의 시간적 연속성을 이용한 적응적 움직임 추정 알고리즘을 제안한다. 기존의 전역 탐색 방법 (FSA)에서와 같이 정방형의 전역 탐색 영역 (GSR)을 정하고, GSR 안에 시간적으로 인접한 블록들의 움직임 벡터들로 예측한 비정방형의 적응적 국부 탐색 영역 (LSR)들을 정한다. 여기서 시간적으로 인접한 블록은 이전 프레임의 블록 중 움직임 벡터로 볼 때 현재 프레임에 시간적으로 움직임이 연속될 가능성이 있는 블록이다. 그리고 이 LSR들로 만든 영역에 대해서만 움직임 탐색을 행하여 탐색의 정확성을 높이고 탐색 시간을 줄일 수 있다. 모의 실험 결과, 제안한 방법은 기존의 탐색 방법들에 비해 탐색 영역을 줄여 계산량을 현저히 낮추면서도 우수한 화질을 보였다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권9호
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• pp.552-561
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• 2004

This paper is concerned with a new speed sensorless induction motor scheme which can be successfully applied to at any speed including even zero speed. The proposed method is robust against rotor resistance variations. In addition, simultaneous on-line estimations of speed and rotor resistance are realized based on a feedforward type torque control approach. The rotor flux with a low frequency sinusoidal waveform has been utilized to help the simultaneous estimation for both speed and rotor resistance. The control scheme has no current minor loop to determine voltage references. Since the proposed estimation does not depend on any derivative terms of currents and stator voltages, it offers a good performance at extremely low speed region for sensorless induction motor. Furthermore, the proposed control is simply using motor parameters and stator currents without determining any PI gains for current feedback and any signal injection for the rotor resistance estimation. Finally, both simulation and experimental results are given to show the effectiveness of this method.

• 응용통계연구
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• 제13권2호
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• pp.353-369
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• 2000

관찰 단위들간 특정한 공간 종속관계를 지닌 공간모집단에서 사각형의 칸들로 분할한 후 각 칸마다 하나의 표본점을 임의추출하여 관심 변수의 모수를 추정할 때 탐색 관찰조건을 만족하는 인접한 표본단위만을 추가 관찰하여 모수를 추정하는 적합탐색 추정 방법을 층화 공간표본설계에 적용시켜 보았다. 모의자료를 설정한 가상의 2차원 공간모집단을 층화 공간표본설계에 의해 층화시킨 후 적합 탐색 추정방법을 적용시켜 본 결과, 단순히 공간모집단을 분할하는 전통적인 공간표본설계보다 적은 수의 표본이 관찰되었으며, 효율성이 크게 감소하지 않는 결과를 얻음으로써 층화효과와 적합탐색 관찰효과가 동시에 존재하는 적절한 추정 결과를 얻을 수 있었다.