Machine vision system for quantification of cotton fiber length and maturity

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Title: Machine vision system for quantification of cotton fiber length and maturity
Author: Shahriar, Muneem
Abstract: Cotton is an important cash crop in the United States (third producer , first exporter ) . There is a constant demand for high quality cotton fibers in the export market , especially for fiber length and maturity . This requires an ever moving research into methodologies that can measure these qualities from cotton fibers accurately and quickly . In a previous study , a fiber length algorithm was developed to measure the length of cotton fibers with good accuracy (+ / - 1 % of true length ) and was validated on 20 cotton samples totaling 10 ,000 fibers . The objective of this thesis is to develop a machine vision system for the quantification of both fiber length and maturity . To achieve this , an improved image acquisition system is proposed which acquires high -resolution (25 ,400 dpi ) longitudinal scans of complete cotton fibers without breaking the fibers into individual segments or applying any physical stress to straighten them . Software algorithms are implemented on these scans to extract features related to fiber length and maturity . For length measurement , Wang ~{! / ~}s length algorithm is employed because it is invariant to fiber shapes , intra -fiber crimps and inter -fiber intersections . However , modifications have been made primarily to enhance the computational speed of the algorithm so that length measurements are close to real -time . The modified algorithm has also been validated on the original 20 cotton samples . An indirect method of estimating fiber maturity based on the evaluation of cotton fiber characteristics is also proposed . The maturity algorithm measures changes in fiber width , fiber convolutions , and fiber translucency along the length of a fiber and creates features that are pertinent to study these characteristics in more detail . The proposed algorithm has been applied to a sample of 50 mature and 50 immature cotton fibers . The results indicate that all three fiber haracteristics show statistically significant differences between the two samples . Further analysis has also shown that some features such as thin places per -unit -length and intensity differences are excellent predictors of maturity . The least deterministic characteristic found is changes in fiber width . To conclude , the findings imply that the system is fully capable of measuring fiber length , and capable of quantifying maturity differences between cotton samples .
URI: http : / /hdl .handle .net /2346 /20816
Date: 2008-08


Machine vision system for quantification of cotton fiber length and maturity. Master's thesis, Texas Tech University. Available electronically from http : / /hdl .handle .net /2346 /20816 .

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