Workpiece localization with shadow detection and removing
文献类型：会议论文
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| 作者 | Qin, Zhengke ; Zhu, Wenjun; Wang, Peng; Qiao, Hong
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| 出版日期 | 2013-12 ; 2013-12 ; 2013-12 ; 2013-12 ; 2013-12 |
| 会议日期 | 12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013 ; 12-14 Dec. 2013 |
| 会议地点 | Shenzhen, China ; Shenzhen, China ; Shenzhen, China ; Shenzhen, China ; Shenzhen, China |
| 英文摘要 |
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. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14762]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 作者单位 | Institute of Automaton, Chinese Academy of Science |
| 推荐引用方式 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]. 见:. Shenzhen, China, Shenzhen, China, Shenzhen, China, Shenzhen, China, Shenzhen, China. 12-14 Dec. 2013, 12-14 Dec. 2013, 12-14 Dec. 2013, 12-14 Dec. 2013, 12-14 Dec. 2013. |
入库方式： OAI收割
来源：自动化研究所
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