Title: Chain-chip automatic sorting array method based on computer vision

Authors: Xiao-Hang Shan; Bi-Qing Ye; Li Zhang

Addresses: Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education, Zhejiang University of Technology, Hangzhou 310014, China ' Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education, Zhejiang University of Technology, Hangzhou 310014, China ' Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education, Zhejiang University of Technology, Hangzhou 310014, China

Abstract: The automatic identification and sorting of chain-chip is one of the important technologies in automatic production line. In order to improve the efficiency and automation of the chain-chips arraying and the whole production process, this paper provides a chain-chip automatic sorting array method based on computer vision and Artificial Neural Network (ANN). Firstly, the chain-chip automatic sorting array machine is proposed. Then, on the basis of Hu invariant moment algorithm, the invariant moments of the acquisition image are analysed to gain the characteristic parameters for sorting. The neural network classifier is designed to realise automatic sorting technology of chain-chips. Experiment results show that the first three-order invariant moment can be used as characteristic parameters for chain-chip identification. This method has the advantages of high accuracy, good sampling performance and strong anti-noise ability. It can meet the demands of object identification requirements in complicated environment.

Keywords: automatic sorting; invariant moment; computer vision; neural network.

DOI: 10.1504/IJWMC.2017.085570

International Journal of Wireless and Mobile Computing, 2017 Vol.12 No.4, pp.414 - 418

Received: 25 Jul 2016
Accepted: 12 Feb 2017
Published online: 30 Jul 2017 *

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