Abstract: Cashmere and fine wool have different scale structures,which is a major reference distinguishing them.A method is proposed to distinguish these two type fibers from each other intelligently.After the 8-bit grayscale images of fibers are captured by CCD camera,they are converted to the binary image only having one pixel wide edge using image technology.Then,four primarily comparable parameters describing the scale shape of fibers are extracted from these binary images and the database including them is established.A Bayes classification model,which is used to distinguish cashmere from fine wool,is developed on the basis of statistic hypothesis of four parameters based on the database.The simulation results show that the model is effective in distinguishing cashmere from fine wool,where the classification accuracy rate is 83 percent for cashmere and 90 percent for fine wool,and probably the classification accuracy rate increases with increasing parameters.