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Journal of Electronic Imaging

Graphical processing unit−based machine vision system for simultaneous measurement of shrinkage and soil release in fabrics
Author(s): Sridharan Kamalakannan; Arunkumar Gururajan; Matthew M. Hill; Muneem Shahriar; Hamed Sari-Sarraf; Eric Francois Hequet
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Paper Abstract

We present a machine vision system for simultaneous and objective evaluation of two important functional attributes of a fabric, namely, soil release and shrinkage. Soil release corresponds to the efficacy of the fabric in releasing stains after laundering and shrinkage essentially quantifies the dimensional changes in the fabric postlaundering. Within the framework of the proposed machine vision scheme, the samples are prepared using a prescribed procedure and subsequently digitized using a commercially available off-the-shelf scanner. Shrinkage measurements in the lengthwise and widthwise directions are obtained by detecting and measuring the distance between two pairs of appropriately placed markers. In addition, these shrinkage markers help in producing estimates of the location of the center of the stain on the fabric image. Using this information, a customized adaptive statistical snake is initialized, which evolves based on region statistics to segment the stain. Once the stain is localized, appropriate measurements can be extracted from the stain and the background image that can help in objectively quantifying stain release. In addition, the statistical snakes algorithm has been parallelized on a graphical processing unit, which allows for rapid evolution of multiple snakes. This, in turn, translates to the fact that multiple stains can be detected and segmented in a computationally efficient fashion. Finally, the aforementioned scheme is validated on a sizeable set of fabric images and the promising nature of the results help in establishing the efficacy of the proposed approach.

Paper Details

Date Published: 1 April 2010
PDF: 12 pages
J. Electron. Imag. 19(2) 023009 doi: 10.1117/1.3421977
Published in: Journal of Electronic Imaging Volume 19, Issue 2
Show Author Affiliations
Sridharan Kamalakannan, Texas Tech Univ. (United States)
Arunkumar Gururajan, Texas Tech Univ. (United States)
Matthew M. Hill, Texas Tech Univ. (United States)
Muneem Shahriar, Texas Tech Univ. (United States)
Hamed Sari-Sarraf, Texas Tech Univ. (United States)
Eric Francois Hequet, Texas Tech Univ. (United States)

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