Compact optical instrument for surface classification using self-mixing interference in a laser diode

Sahin Ozdemir, S. Shinohara, S. Ito, S. Takamiya, H. Yoshida

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

A compact and noncontact sensor using the self-mixing interference inside a semiconductor laser is designed to classify moving surfaces. An artificial neural network is employed for the data processing. The results indicate more than 92% correct classification for eight different surfaces of different materials, different manufacturing methods and different surface roughnesses. The accuracy of the system is restricted by the localized irregularities on the surface and the mechanical instabilities of the carrying stage over which the surfaces are placed.

Original languageEnglish (US)
Pages (from-to)38-43
Number of pages6
JournalOptical Engineering
Volume40
Issue number1
DOIs
StatePublished - Jan 1 2001

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

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