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Description:
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This thesis presents a protocol for creating digital images of printed fabric swatches and an algorithm that will automatically measure dimensional changes and segment stains so that soil release could be evaluated . The dimensional changes measured here are shrinkage and skew . Current methods for evaluating dimensional changes on printed fabrics are manual . There are no current methods for evaluation of soil release on printed fabrics and the segmentation that the proposed algorithm provides is a vital first step to such a system . This thesis proposes a system that could become a standard for making both measurements simultaneously . To make these measurements , printed fabric swatches are scanned before and after wash using an off -the -shelf scanner . Reference points (called shrinkage dots ) are placed on the fabric swatches and then located in the scanned images . This is done using image registration and subtraction to remove the influence of the pattern followed by cross -correlation to then locate the shrinkage dots . The locations of the shrinkage dots are used both to calculate the dimensional changes and in locating the stains . Before a snake -based method segments the stain , the influence of the background pattern is removed using the same registration and subtraction method used for shrinkage dot detection . In an experiment involving 240 images and 10 different printed patterns , the algorithm was able to correctly identify 98 .8 % of the shrinkage dots and identify stains in 93 .3 % of stains that were determined to exist according to technicians . The segmentation accuracy is quantified by an average dice metric of .87 in a set of 50 potential stains when comparing to manual segmentations . |