Artificial neural networks for colour prediction in leather dyeing on the basis of a tristimulus system

Abstract

Computer-assisted colour prediction and quality control have become increasingly important to the dyeing process in many consumer goods manufacturing industries, including textile and leather. The most challenging aspect concerns dye recipe prediction for the production of the required shade on a given substrate. Computer recipe prediction based on the conventional and widely used Kubelka-Munk model often fails under a variety of conditions. In the present investigation, an attempt has been made to develop an artificial neural network model to predict colour in terms of tristimulus values (X, Y, Z) given the concentration of dyes. An artificial neural network model was trained with 300 pairs of known input vectors, i.e. dye concentrations, and output vectors, i.e. colour parameters, using a backpropagation algorithm. The artificial neural network topology consists of three neurons in the input layer to represent the concentration of dyes, three neurons in the output layer to represent the tristimulus values X, Y, and Z, and five neurons in the hidden layer with a log-sigmoid transfer function. The artificial neural network results showed a good level of colour prediction during the training and testing phase. The results also indicate that the artificial neural network has the potential to give better predictive performance than the conventional Kubelka-Munk model.

Application of ant colony optimization to color matching of dyed cotton fabrics with direct dyestuffs mixtures

“…[10][11][12] The choice to use one of these two methods is done according to the purpose of matching. 4,8 Other researchers have used artificial intelligence techniques such as neural networks [13][14][15][16][17] and genetic algorithms. 18,19 However no attempts to use the ant colony algorithm to resolve the color recipe prediction problem are available in the literature.…”

Colour recipe prediction using ant colony algorithm: principle of resolution and analysis of performances

“…methods based on colorimetric and spectrophotometric algorithms. [8][9][10] Others applied artificial intelligence techniques such as neural network [11][12][13][14][15][16] and genetic algorithm. 17 Neural network is a computing system inspired by the functioning of biological neurons.…”

“…Li et al 15 applied this method in colour difference detection of fabric and efficiently obtained colour characteristic values. Jawahar et al 16 have used neural network in leather dyeing on the basis of a tristimulus system. They have proved that it is a promising method for colour prediction.…”

Neural network approach to a colorimetric value transform based on a large‐scale spectral dataset

“…The output of the limiter is then broadcast to all of the neurons in the next layer. In the present stage, owing to its superiority in fitting the non‐linearity of complex mathematical issues, this kind of approach is widely used in the colour‐related domain .…”