Aiming at hairiness measurement, a digital image acquisition system is constructed, based on which a novel algorithm is proposed in order to measure the number and length of yarn hairiness. The algorithm can be used to make feature analysis of yarn images captured continuously, and yarn hairiness features for quality evaluation of yarn hairiness are determined. With pretreatment of yarn image, including gray-scale transformation, background subtraction, image enhancement, dynamic threshold segmentation, tilt correction, image denoising and image segmentation, yarn hairiness image is obtained. Then the yarn hairiness image is treated by using thinning algorithm, so the thinned yarn hairiness image is obtained. With yarn axis and the margin of trunk as reference, and with proper baseline, yarn hairiness image skeleton is extracted at the pixel level, and the number of yarn hairiness of different length is determined by statistics. Experimental results show that the precision of the new method is consistent with the visual observation method, and its deviation is within 5%. The method can improve the efficiency and accuracy of yarn hairiness feature extraction.