Classifying coloured objects under different lighting conditions using the HSV colour model and a neural network

This paper reports on the results obtained when using Radial Basis Neural Networks to classify different objects using only colour data extracted from images captured under different lighting conditions. Each network is trained with data from a single image and then tested with data from images containing the same collection of objects, but captured under different lighting conditions. The ability of the neural networks to generalize is tested to see how well it can recognise the objects when the ambient light source is changed. Results relating to the classification success of each of the networks are presented.