An efficient method for solid-colour and multicolour region segmentation in real yarn-dyed fabric images

This paper presents an efficient approach to solid-colour and multicolour region segmentation in real yarn-dyed fabric images. The approach is based on a novel model describing the spectral response of a multispectral imaging system to yarn-dyed fabrics. The model indicates that solid-colour regions cannot be distinguished from multicolour regions in terms of reflectance, tristimulus, or CIELAB values owing to a geometric term representing the influence of fabric surface condition on measured colours. The geometric term makes it difficult to determine the segmentation thresholds of CIEXYZ and CIELAB colour histograms. However, solid-colour and multicolour regions can be detected in CIExyY space because chromaticity coordinates are impervious to the geometric term. The CIExyY histograms of a solid-colour region accord with one Gaussian distribution, but those of a multicolour region accord with a combination of two Gaussian distributions. The CIEXYZ, CIELAB, and CIExyY colour distributions of both solid-colour and multicolour yarn-dyed fabrics were analysed in detail in simulation and real experiments. Experimental results show that solid-colour yarn-dyed regions can be distinguished from multicolour yarn-dyed fabric regions by the shapes of CIExyY histograms, but cannot be distinguished by the shapes of CIEXYZ or CIELAB histograms.