An objective pilling evaluation method has been developed using image analysis and artificial neural network. Pilling parameters obtained in the previous study were used as the input values for neural network. A total of 9 data sets including 5 standard grades and 4 interpolated intermediate grades were used for training the network. Nine samples were prepared to verify the validity of the trained network in comparison with the subjective evaluation results. 18 woven and 12 knitted samples were tested to investigate the effect of the fabric structure on the performance of the network. Finally, 55 woven fabric samples were tested to evaluate the performance of the newly developed method and it was proven to be suitable for the evaluation of pilling grade especially for woven fabrics.