Focusing on soft-computing techniques to model the role of context in determining colours

This paper describes an initial study to investigate the role of context in determining colours from a machine learning perspective. A soft-computing technique in the form of fuzzy neural networks is used to perform the intelligent processing of categorising colours given some training. The main hypothesis suggests that the neural network will not perform as well as a human familiar with the NCS colour space, because humans possess context knowledge needed to correctly classify any colour variety into eleven groupings. This paper describes the process taken to create the dataset suitable for the network, and reports on the use of the software called FuzzyCOPE 3/sup /spl copy// to investigate this hypothesis. Further, it points to issues such as what is context knowledge? Can the network's learning be said to possess contextual knowledge of the colour space?.