Study for Workpiece Identity Based on the BP Neural Network and the Zernike Moment

Xian Wei; Jing Dong Zhang; Xue Mei Qi

doi:10.4028/www.scientific.net/AMR.694-697.1958

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697Study for Workpiece Identity Based on the BP...

Study for Workpiece Identity Based on the BP Neural Network and the Zernike Moment

Abstract:

The robots identify, locate and install the workpiece in FMS system by identifying the characteristic information of target workpiece. The paper studied the recognition technology of complex shape workpiece with combination of BP neural network and Zernike moment. The strong recognition ability of Zernike moment can extract the characteristic. The good fault tolerance, classification, parallel processing and self-learning ability of BP neural network can greatly improve the accurate rate of recognition. Experimental results show the effectiveness of the proposed method.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

1958-1963

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.1958

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Online since:

May 2013

Authors:

Xian Wei, Jing Dong Zhang, Xue Mei Qi

Keywords:

FMS, Neural Network (NN), Visual Identity, Zernike Moment

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