Experiments in colour texture analysis

In this paper we focus on the classi®cation of colour texture images. The main objective is to determine the contribution of colour information to the overall classi®cation performance. Three relevant approaches to grey scale texture analysis, namely local linear transforms, Gabor ®ltering and the co-occurrence approach are extended to colour images. They are evaluated in a quantitative manner by means of a comparative experiment on a set of colour images. We also investigate the e€ect of using di€erent colour spaces and the contribution of colour and texture features separately and collectively. The evaluation criteria is the classi®cation accuracy using a neural network classi®er based on Learning Vector Quantization. Experimental results indicate that the incorporation of colour information enhances the performance of the texture analysis techniques examined.