Fabric colour measurement in the small region of CIELab colour space using a scanner-based subtractive clustering fuzzy inference system

Digital devices are increasingly being used in the colour measurement of textile-made materials. Proper scanner characterisation is crucial for accurate and consistent colour measurement. In the present study a fuzzy inference system based on subtractive clustering, called FIS_SC method, for the colorimetric characterisation of a scanner to measure the colour of the fabrics in a small region of a colour space is proposed. The results of the proposed method for 16 colour sets were obtained and compared with the results of the scanner characterisation using polynomial regression and neural network method. It was shown that the FIS_SC method successfully characterised the scanner in the small colour space, so that its mean of the colour difference was lower than the polynomial regression and neural network methods in almost all colour sets.