1 January 2001 Compact optical instrument for surface classification using self-mixing interference in a laser diode
Sahin Kaya Ozdemir, Shigenobu Shinohara, Satoshi Ito, Hirofumi Yoshida
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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.
©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)
Sahin Kaya Ozdemir, Shigenobu Shinohara, Satoshi Ito, and Hirofumi Yoshida "Compact optical instrument for surface classification using self-mixing interference in a laser diode," Optical Engineering 40(1), (1 January 2001). https://doi.org/10.1117/1.1331268
Published: 1 January 2001
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Cited by 29 scholarly publications.
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KEYWORDS
Semiconductor lasers

Speckle

Neurons

Surface finishing

Time metrology

Optical components

Signal detection

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