Preliminary validation of a fabric smoothness assessment system

Chris Turner, Hamed Sari-Sarraf, Eric Hequet, Sunho Lee

Research output: Contribution to journalConference articlepeer-review


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 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.

Original languageEnglish
Pages (from-to)140-148
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2003
EventSixth International Conference on Quality Control by Artificial Vision - Gatlinburg, TN, United States
Duration: May 19 2003May 22 2003


  • Adaptive smoothing
  • Fabric smoothness
  • Facet model
  • Smart cameras
  • Surface profiling


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