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Precision Work-piece Detection and Measurement Combining Top-down and Bottom-up Saliency

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Abstract

In this paper, a fast and accurate work-piece detection and measurement algorithm is proposed based on top-down feature extraction and bottom-up saliency estimation. Firstly, a top-down feature extraction method based on the prior knowledge of workpieces is presented, in which the contour of a work-piece is chosen as the major feature and the corresponding template of the edges is created. Secondly, a bottom-up salient region estimation algorithm is proposed, where the image boundaries are labelled as background queries, and the salient region can be detected by computing contrast against image boundary. Finally, the calibration method for vision system with telecentric lens is discussed, and the dimensions of the work-pieces are measured. In addition, strategies such as image pyramids and a stopping criterion are adopted to speed-up the algorithm. An automatic system embedded with the proposed detection and measurement algorithm combining top-down and bottom-up saliency (DM-TBS) is designed to pick out defective work-pieces without any manual auxiliary. Experiments and results demonstrate the effectiveness of the proposed method.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Nos. 61379097, 91748131, 61771471, U1613213 and 61627808), National Key Research and Development Plan of China (No. 2017YFB1300202), and Youth Innovation Promotion Association Chinese Academy of Sciences (CAS) (No. 2015112).

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Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Jia Sun, Peng Wang, Yong-Kang Luo, Gao-Ming Hao & Hong Qiao

  2. University of Chinese Academy of Sciences, Beijing, 100190, China

    Jia Sun

Authors
  1. Jia Sun
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  2. Peng Wang
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  3. Yong-Kang Luo
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  4. Gao-Ming Hao
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  5. Hong Qiao
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Corresponding author

Correspondence to Peng Wang.

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Recommended by Associate Editor Jangmyung Lee

Jia Sun received the B. Sc. degree in the measurement and control technology and instrument from North University of China, China in 2009, and the M. Sc. degree in instrument science and technology from the Beijing Institute of Technology, China in 2012. She is currently a Ph. D. degree candidate in control theory and control engineering at Institute of Automation, Chinese Academy of Sciences, China.

Her research interests include robot vision, precise assembly, and camera calibration.

Peng Wang received the B. Sc. degree in electrical engineering and automation from Harbin Engineering University, China in 2004, the M. Sc. degree in automation science and engineering from Harbin Institute of Technology, China in 2007, and the Ph. D. degree in control theory and control engineering from Institute of Automation, Chinese Academy of Sciences, China in 2010. He is currently a professor with Institute of Automation, Chinese Academy of Sciences, China.

His research interests include intelligent robot, industrial robot, robotic assembly, robotic vision, image processing and visual perception model.

Yong-Kang Luo received the Ph. D. degree in control theory and control engineering from University of Chinese Academy of Sciences, China in 2016. He is currently a research assistant at Institute of Automation, Chinese Academy of Sciences, China.

His research interests include computer vision, machine learning, and robotics.

Gao-Ming Hao received the B. Sc. degree in mechanical engineering and automation from Shijiazhuang Tiedao University, China in 2011, and the M. Sc. degree in materials processing engineering from China Academy of Machinery Science and Technology, China in 2014. He is currently working in Institute of Automation, Chinese Academy of Sciences, China.

His research interests include robotics, precise assembly, automatic optic inspection (AOI) equipment.

Hong Qiao received the B. Eng. degree in hydraulics and control, the M. Eng. degree in robotics from Xi’an Jiaotong University, China, the M.Phil. degree in robotics control from Industrial Control Center, University of Strathclyde, Strathclyde, UK, and the Ph. D. degree in robotics and artificial intelligence from De Montfort University, UK in 1995. She was a research assistant professor from 1997 to 2000 and an assistant professor from 2000 to 2002 with the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, China. In 2002, she joined as a lecturer with School of Informatics, University of Manchester, UK. She is currently a professor with State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

Her research inferests include intelligent robot, industrial robot, robotic assembly, robotic vision, image processing and visual perception model.

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Sun, J., Wang, P., Luo, YK. et al. Precision Work-piece Detection and Measurement Combining Top-down and Bottom-up Saliency. Int. J. Autom. Comput. 15, 417–430 (2018). https://doi.org/10.1007/s11633-018-1123-1

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