Using neural networks for fiber content analysis

For a number of years fiber content analysis has presented a challenging problem because of the complexity of the contents of textile material. This work is much needed for automated systems which ideally should be able to identify nondestructively the fiber content by using the acquired images. This paper presents the use of neural networks for fiber content analysis. More specifically the discrimination between the cashmere fiber and the wool fiber is considered. Neural networks are particularly suitable for fusing different features to maximize the classification performance which is presented in the paper