Colour space conversion model from CMYK to CIELab based on CS‐WNN

Abstract

AbstractIn the process of colour space conversion from CMYK to CIELab, colour difference will be caused, which has a negative impact on the quality of digital printing products. In this article, an improved wavelet neural network (WNN) model optimised by cuckoo search (CS) algorithm is proposed to reduce the colour difference. Initially, the colour space conversion model based on WNN is established. The CS algorithm is used to optimise the initial weights and parameters of dilation and translation in the WNN model. Then, 1296 samples are made to train the CS‐WNN model. Finally, 100 test samples are input into the trained network to obtain the corresponding L, a and b values of CIELab. The experimental results show that the average conversion colour difference () of the proposed model is 3.469. The conversion accuracy and stability of the proposed model are better than the traditional neural network.