Paper
1 May 2003 Preliminary validation of a fabric smoothness assessment system
Author Affiliations +
Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.514953
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States
Abstract
A fabric's tendency to wrinkle is vitally important to the textile industry as it impacts the visual appeal of apparels. Current methods of grading this characteristic, called fabric smoothness, are very subjective and inadequate. As such, a quantitative method for assessing fabric smoothness is of the utmost importance to the textile community. To that end, we have proposed a laser-based surface profiling system that utilizes a smart camera to sense the 3-D topography of the fabric specimens. The system incorporates methods based on anisotropic diffusion and the facet model for characterizing edge information that ultimately relate to a specimen's degree of wrinkling. In this paper, we detail the initial steps in a large-scale validation of this system. Using histograms of the extracted features, we compare the output of the system among 78 swatches of various color, type, and texture. The results show consistency among repeated scans of the same swatch as well as among different swatches taken from the same fabric sample. Also, since swatches taken from the same piece of fabric typically wrinkle similarly, this adds to the feasibility of the system. In other words, it adequately identifies and measures appropriate features of the wrinkles found on a sample.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chris Turner, Hamed Sari-Sarraf, Eric F. Hequet, and Sunho Lee "Preliminary validation of a fabric smoothness assessment system", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.514953
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Cited by 1 scholarly publication.
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KEYWORDS
Cameras

Imaging systems

Profiling

3D modeling

Laser systems engineering

Visualization

Edge detection

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