Texture classification system using colour space fusion

A novel colour texture classification system is presented based on an ensemble of independent classifiers each assigned to a different colour representation model. Gaussian Markov random fields features are used in a study to illustrate this previously unexplored approach and its potential to combine information from different colour spaces to improve accuracy. Experimental results illustrate that colour space information fusion results in significant improvements in accuracy.