Dimensional change measurement and stain segmentation in printed fabrics

Matthew Hill, Sridharan Kamalakannan, Arunkumar Gururajan, Hamed Sari-Sarraf, Eric Hequet

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Dimensional changes and soil release are important functional attributes of fabrics that impact their pricing in the marketplace. This paper presents the underlying principles of a machine vision system that creates a framework for making both measurements in a simultaneous and automatic fashion from digitized fabric images. In addition, the proposed approach is equipped to operate on solid color, as well as printed/patterned fabrics. This system, using image analysis, can (i) measure dimensional changes, which include shrinkage and skew, and (ii) localize stains on the fabric image, which can then be evaluated for soil release. Robust extraction of the above measurements on printed fabric images are made possible using a sequence of customized image registration and background-subtraction techniques. The system was validated using a set of 623 fabric images that involved the detection of 1868 shrinkage dots which were used to make 934 shrinkage measurements, 467 skew measurements, and detect 240 potential stains. The system produced excellent results with a successful shrinkage dot detection rate of 98.9% and an average stain segmentation accuracy of 0.87 using the dice metric.

Original languageEnglish
Pages (from-to)1655-1672
Number of pages18
JournalTextile Research Journal
Issue number16
StatePublished - Oct 2011


  • Printed fabric
  • image analysis
  • image registration
  • segmentation
  • shrinkage
  • soil release


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