Graphical processing unit-based machine vision system for simultaneous measurement of shrinkage and soil release in fabrics

Sridharan Kamalakannan; Arunkumar Gururajan; Matthew M. Hill; Muneem Shahriar; Hamed Sari-Sarraf; Eric Francois Hequet

doi:10.1117/1.3421977

1 April 2010 Graphical processing unit−based machine vision system for simultaneous measurement of shrinkage and soil release in fabrics

Sridharan Kamalakannan, Arunkumar Gururajan, Matthew M. Hill, Muneem Shahriar, Hamed Sari-Sarraf, Eric Francois Hequet

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 2, 023009 (April 2010). https://doi.org/10.1117/1.3421977

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.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Sridharan Kamalakannan, Arunkumar Gururajan, Matthew M. Hill, Muneem Shahriar, Hamed Sari-Sarraf, and Eric Francois Hequet "Graphical processing unit−based machine vision system for simultaneous measurement of shrinkage and soil release in fabrics," Journal of Electronic Imaging 19(2), 023009 (1 April 2010). https://doi.org/10.1117/1.3421977

Published: 1 April 2010

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