Identification of tools with failure barcode based on multi-information fusion

Jia Jing Wang, Zhu Sheng Zhang, Wei Ping He

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A multi information fusion classification and identification system was proposed in view of the fact that traditional tool identification methods suffered from inefficiency and being susceptible to the bar code failure due to inadequate protection, pollution and other factors in the process of complex production and circulation. First, this system quantized tool features, such as shape, texture, weight and other characteristics, from image sensors and weight sensors. Then, high dimension features vector from both training and testing samples of tool and bar code was extracted. Finally the failure barcode was obtained with the algorithms of support vector machine and Dempster-Shafer. The experimental results show that the system could classify and identify the tool of destructive bar code accurately and effectively which can satisfy the actual requirement in production.

Original languageEnglish
Pages (from-to)1675-1680
Number of pages6
JournalShanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University
Volume48
Issue number12
StatePublished - 28 Dec 2014

Keywords

  • Dempster-shafer (D-S)
  • Feature extraction
  • Multi-information fusion
  • Support vector machine (SVM)
  • Tool identification

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