Workpiece localization with shadow detection and removing; Workpiece localization with shadow detection and removing; Workpiece localization with shadow detection and removing; Workpiece localization with shadow detection and removing; Workpiece localization with shadow detection and removing
Qin, Zhengke; Zhu, Wenjun; Wang, Peng; Qiao, Hong
2013-12 ; 2013-12 ; 2013-12 ; 2013-12 ; 2013-12
Conference NameRobotics and Biomimetics (ROBIO), 2013 IEEE International Conference on ; Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on ; Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on ; Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on ; Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on
Conference Date12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013
Conference PlaceShenzhen, China ; Shenzhen, China ; Shenzhen, China ; Shenzhen, China ; Shenzhen, China
Abstract
This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.
;
This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.
;
This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.
;
This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.
;
This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14762
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
AffiliationInstitute of Automaton, Chinese Academy of Science
Recommended Citation
GB/T 7714
Qin, Zhengke,Zhu, Wenjun,Wang, Peng,et al. Workpiece localization with shadow detection and removing, Workpiece localization with shadow detection and removing, Workpiece localization with shadow detection and removing, Workpiece localization with shadow detection and removing, Workpiece localization with shadow detection and removing[C],2013, 2013, 2013, 2013, 2013.
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