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Optical Engineering • Open Access

Fusing multifocus images for yarn hairiness measurement
Author(s): Rongwu Wang; Jinfeng Zhou; Lingjie Yu; Bugao Xu

Paper Abstract

Yarn hairiness has been an important indication of yarn quality that affects weaving production and fabric appearance. In addition to many dedicated instruments, various image analysis systems have been adopted to measure yarn hairiness for potential values of high accuracy and low cost. However, there is a common problem in acquiring yarn images; that is, hairy fibers protruding beyond the depth of field of the imaging system cannot be fully focused. Fuzzy fibers in the image inevitably introduce errors to the hairiness data. This paper presents a project that attempts to solve the off-focus problem of hairy fibers by applying a new imaging scheme—multifocus image fusion. This new scheme uses compensatory information in sequential images taken at the same position but different depths to construct a new image whose pixels have the highest sharpness among the sequential images. The fused image possesses clearer fiber edges, permitting more complete fiber segmentation and tracing. In the experiments, we used six yarns of different fiber contents and spinning methods to compare the hairiness measurements from the fused images with those from unfused images and from the Uster tester.

Paper Details

Date Published: 2 December 2014
PDF: 7 pages
Opt. Eng. 53(12) 123101 doi: 10.1117/1.OE.53.12.123101
Published in: Optical Engineering Volume 53, Issue 12
Show Author Affiliations
Rongwu Wang, Donghua Univ. (China)
Jinfeng Zhou, Donghua Univ. (China)
Lingjie Yu, Donghua Univ. (China)
Bugao Xu, Donghua Univ. (China)
The Univ. of Texas at Austin (United States)

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