Measurement of long yarn hair based on hairiness segmentation and hairiness tracking

Abstract

For the problem of hairiness information missed in existing hairiness measurement method, the goal of this work is to accurately measure the length of long yarn hairiness and obtain the path over every hairiness point of the whole hairiness. To achieve this goal, the yarn images were captured by the video microscope (MOTIC) and the thinned hairiness images were obtained by a series of image processing. The different measurement baseline and step value were choose to segment long hairiness in the method of hairiness segmentation, and the different hairiness lengths were obtained, the results of length show that the length of 0.5mm (baseline)and 3 pixels (step value) is closest to hairiness real length. And then, the more accurate lengths of the hairiness were calculated by the method of hairiness tracking. The lengths of the two new methods are longer than the length of the method of fixed length (1mm), but the lengths of hairiness tracking is longer than the longest lengths of hairiness segmentation. The compared results show that the method of hairiness tracking can record the information of every point in hairiness and calculate the pixels of a hair fiber, and acquire more complete information of full hairiness then hairiness segmentation.

Keywords:

• Long yarn hair
• digital image technology
• hairiness segmentation
• hairiness tracking
• hairiness path

Acknowledgments

The authors would like to thank the anonymous reviewers and the handling associate editor for their insightful comments.