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

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 m ore than 92% correct classification for eight different surfaces of differe nt materials, different manufacturing methods and different surface roughne sses. The accuracy of the system is restricted by the localized irregularit ies on the surface and the mechanical instabilities of the carrying stage o ver which the surfaces are placed. (C) 2001 Society of Photo-Optical Instru mentation Engineers.