Image segmentation based on a Gaussian model applied to pilling evaluation in fabrics

Wear and tear generate fluffiness and pills that remain in the web surface spoiling the appearance of a fabric. In quality control of textiles it is necessary to have an objective method to measure pilling that improves current methods based on visual estimations of the degree of pilling by experts. Image processing techniques have been already proposed for an objective measurement of the degree of pilling. In this work we optimise a method for pilling evaluation based on image analysis that we proposed recently. The method combined operations in both the frequency and the spatial domains in order to better segment pills from the textured web background. We considered a logarithmic in base two relationship between the area of pilling and the degree of pilling based on the human perception mechanisms.