Fabric wrinkle evaluation using laser triangulation and neural network classifier

Wrinkling is one of the most important fabric performance properties, which are routinely evaluated in reference to a set of visual standards in the t extile industry. The visual evaluation is unreliable and time-inefficient. An industrial need for objective and automatic evaluation methods has been increasing markedly in the recent years. An image analysis system is develo ped to meet this need. The laser line triangulation method is used to measu re the 3Dsurface data of a wrinkled fabric, and a neural network is built t o execute the wrinkle classification with respect to the visual standard. D ue to the directionality of wrinkles, a rotary stage is used to change the sample's orientation under the camera so that multiple images of the sample can be captured at different angles and more wrinkle data can be extracted for classification. The wrinkle classifications provided by the system are highly consistent with the visual standards, showing the potential for rep lacing human graders in fabric wrinkling evaluations. (C) 1999 Society of P hoto-Optical Instrumentation Engineers. [S0091-3286(99)01810-3].