Analysing the Creasing Properties of Fabric

Abstract

A large clothing retail store wishes to quantify the creasing properties of the fabrics used in shirts, blouses, dresses, etc. Hitherto, creasing has been judged subjectively and inaccurately, by comparing a sample with carefully designed models, photographs, etc. There is a need for a more objective measurement than this provides and a laboratory-based vision system to automate this task has been proposed. A sample of plain unprinted fabric is first creased in a standard way and then stretched gently as it is placed onto a table. Lighting at a low angle is then applied from one side. The image generated in this way has a low contrast but it is sufficient to allow the crease furrows to be seen. Results are presented for several non-linear filters that convert the grey-scale texture image to binary form. Measurements describing the resulting binary texture are defined. A multi-element vector created by combining several such measurements is then presented to a Pattern Recognition system. This is then trained to identify the creasing coefficient defined by the existing human inspector.