• 제목/요약/키워드: desired image

검색결과 395건 처리시간 0.025초

Corridor Navigation of the Mobile Robot Using Image Based Control

  • Han, Kyu-Bum;Kim, Hae-Young;Baek, Yoon-Su
    • Journal of Mechanical Science and Technology
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    • 제15권8호
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    • pp.1097-1107
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    • 2001
  • In this paper, the wall following navigation algorithm of the mobile robot using a mono vision system is described. The key points of the mobile robot navigation system are effective acquisition of the environmental information and fast recognition of the robot position. Also, from this information, the mobile robot should be appropriately controlled to follow a desired path. For the recognition of the relative position and orientation of the robot to the wall, the features of the corridor structure are extracted using the mono vision system, then the relative position, the offset distance and steering angle of the robot from the wall, is derived for a simple corridor geometry. For the alleviation of the computation burden of the image processing, the Kalman filter is used to reduce search region in the image space for line detection. Next, the robot is controlled by this information to follow the desired path. The wall following control scheme by the PD control scheme is composed of two control parts, the approaching control and the orientation control, and each control is performed by steering and forward-driving motion of the robot. To verify the effectiveness of the proposed algorithm, the real time navigation experiments are performed. Through the result of the experiments, the effectiveness and flexibility of the suggested algorithm are verified in comparison with a pure encoder-guided mobile robot navigation system.

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레벨셋을 이용한 특정 영역의 영상 세그먼테이션 (Image Segmentation of Special Area Using the Level Set)

  • 주기세;조덕상
    • 한국정보통신학회논문지
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    • 제14권4호
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    • pp.967-975
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    • 2010
  • 영상 세그먼테이션은 배경으로부터 객체들을 구별하는 것으로서, 영상 분석과 해석을 하는데 있어서 첫 번째 단계에 해당한다. 그러나 활성 외곽선 모델은 위상이 2개밖에 없으므로 정확하게 원하는 객체들을 추출할 수가 없다. 본 논문에서 원하는 특정한 범위의 명암도를 갖는 객체들을 추출하기 위해서 초기 곡선을 객체들 근처에 구성함으로써 바라는 윤곽을 찾는 방법을 제안한다. 초기 곡선은 히스토그램 평활화, 가우시안 평활화, 임계치를 이용하여 구한다. 제안한 방법은 초기 곡선을 관심영역에 최대 근접시키므로 계산 속도를 줄이고 원하는 영역을 정확하게 추출할 수 있다. CT 영상과 MR 영상에 적용한 결과 제안한 방법이 활성 외곽선 모델보다 더 효과적임을 보였다.

가상 환경에서의 딥러닝 기반 폐색영역 검출을 위한 데이터베이스 구축 (Construction of Database for Deep Learning-based Occlusion Area Detection in the Virtual Environment)

  • 김경수;이재인;곽석우;강원율;신대영;황성호
    • 드라이브 ㆍ 컨트롤
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    • 제19권3호
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    • pp.9-15
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    • 2022
  • This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

Controlling robot by image-based visual servoing with stereo cameras

  • Fan, Jun-Min;Won, Sang-Chul
    • 한국정보기술응용학회:학술대회논문집
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    • 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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    • pp.229-232
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    • 2005
  • In this paper, an image-based "approach-align -grasp" visual servo control design is proposed for the problem of object grasping, which is based on the binocular stand-alone system. The basic idea consists of considering a vision system as a specific sensor dedicated a task and included in a control servo loop, and we perform automatic grasping follows the classical approach of splitting the task into preparation and execution stages. During the execution stage, once the image-based control modeling is established, the control task can be performed automatically. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories by using the Jacobian matrix, which is proved by the Lyapunov stability theory. And we also stress the importance of projective invariant object/gripper alignment. The alignment between two solids in 3-D projective space can be represented with view-invariant, more precisely; it can be easily mapped into an image set-point without any knowledge about the camera parameters. The main feature of this method is that the accuracy associated with the task to be performed is not affected by discrepancies between the Euclidean setups at preparation and at task execution stages. Then according to the projective alignment, the set point can be computed. The robot gripper will move to the desired position with the image-based control law. In this paper we adopt a constant Jacobian online. Such method describe herein integrate vision system, robotics and automatic control to achieve its goal, it overcomes disadvantages of discrepancies between the different Euclidean setups and proposes control law in binocular-stand vision case. The experimental simulation shows that such image-based approach is effective in performing the precise alignment between the robot end-effector and the object.

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AUTOMATIC SELECTION AND ADJUSTMENT OF FEATURES FOR IMAGE CLASSIFICATION

  • Saiki, Kenji;Nagao, Tomoharu
    • 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".

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로봇의 운동특성을 고려한 새로운 시각구동 방법 (A novel visual servoing techniques considering robot dynamics)

  • 이준수;서일홍;김태원
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.410-414
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    • 1996
  • A visual servoing algorithm is proposed for a robot with a camera in hand. Specifically, novel image features are suggested by employing a viewing model of perspective projection to estimate relative pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a, commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

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조립용 로봇의 오프라인 교시를 위한 영상 정보의 이용에 관한 연구 (Utilization of Vision in Off-Line Teaching for assembly robot)

  • 안철기
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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    • pp.543-548
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    • 2000
  • In this study, an interactive programming method for robot in electronic part assembly task is proposed. Many of industrial robots are still taught and programmed by a teach pendant. The robot is guided by a human operator to the desired application locations. These motions are recorded and are later edited, within the robotic language using in the robot controller, and play back repetitively to perform robot task. This conventional teaching method is time-consuming and somewhat dangerous. In the proposed method, the operator teaches the desired locations on the image acquired through CCD camera mounted on the robot hand. The robotic language program is automatically generated and downloaded to the robot controller. This teaching process is implemented through an off-line programming software. The OLP is developed for an robotic assembly system used in this study. In order to transform the location on image coordinates into robot coordinates, a calibration process is established. The proposed teaching method is implemented and evaluated on an assembly system for soldering electronic parts on a circuit board. A six-axis articulated robot executes assembly task according to the off-line teaching in the system.

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Image Sequence Stabilization Scheme Using FIR Filtering

  • Kim, Pyung-Soo
    • International Journal of Control, Automation, and Systems
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    • 제1권4호
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    • pp.515-519
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    • 2003
  • This paper proposes a new image sequence stabilization (ISS) scheme based on filtering of absolute frame positions. The proposed ISS scheme removes undesired motion effects in real-time, while preserving desired gross camera displacements. The well-known finite impulse response (FIR) filter is adopted for filtering. The proposed ISS scheme provides a filtered position and velocity with fine inherent properties. It is demonstrated that the filtered position is not affected by the constant velocity. It is also shown that the filtered velocity is separated from the position. Via numerical simulations, the performance of the proposed scheme is shown to be superior to the existing Kalman filtering scheme.

퍼지 시스템과 Particle Swarm Optimization(PSO)을 이용한 Prewarping 기술 (Prewarping Techniques Using Fuzzy system and Particle Swarm Optimization)

  • 장우석;강환일
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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    • pp.272-274
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    • 2006
  • In this paper, we concentrate on the mask design problem for optical micro-lithography. The pre-distorted mask is obtained by minimizing the error between the designed output image and the projected output image. We use the particle swarm optimization(PSO) and fuzzy system to insure that the resulting images are identical to the desired image. Our method has good performance for the iteration number by an experiment.

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Immediate solution of EM algorithm for non-blind image deconvolution

  • Kim, Seung-Gu
    • Communications for Statistical Applications and Methods
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    • 제29권2호
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    • pp.277-286
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    • 2022
  • Due to the uniquely slow convergence speed of the EM algorithm, it suffers form a lot of processing time until the desired deconvolution image is obtained when the image is large. To cope with the problem, in this paper, an immediate solution of the EM algorithm is provided under the Gaussian image model. It is derived by finding the recurrent formular of the EM algorithm and then substituting the results repeatedly. In this paper, two types of immediate soultion of image deconboution by EM algorithm are provided, and both methods have been shown to work well. It is expected that it free the processing time of image deconvolution because it no longer requires an iterative process. Based on this, we can find the statistical properties of the restored image at specific iterates. We demonstrate the effectiveness of the proposed method through a simple experiment, and discuss future concerns.