X-ray microtomographic image analysis for identification of cotton contaminants

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Title: X-ray microtomographic image analysis for identification of cotton contaminants
Author: Pai, Ajay S
Abstract: Technologies currently used for cotton contaminant assessment suffer from some fundamental limitations . These limitations severely restrict the ability of existing technologies to accurately detect and classify contaminants in cotton . Such inaccuracies result in the misassessment of the cotton quality , and have a serious impact on its economic value . The fundamental limitations of existing methods include the inability to detect contaminants under the surface of cotton , the inability to accurately measure shapes and sizes , sample preparation requirements , and poor spatial resolution . These limitations may be easily overcome by the use of x -ray tomographic imaging , which allows for highly accurate imaging of the internal features of an object in a non -destructive fashion . This thesis describes in detail the design of a GUI based interactive cotton contaminant analysis tool . Through the use of an x -ray microtomographic scanner and image processing algorithms , it is shown that x -ray tomographic imaging can provide very accurate information regarding shape , size , and density of cotton contaminants . This information has been analyzed using a fuzzy -logic -based classification scheme to create a highly accurate contaminant analysis tool . Despite its obvious advantages , x -ray imaging does have some drawbacks , principle among which pertains to the time taken to perform the procedure . These drawbacks , along with possible solutions have also been discussed in this thesis . It is our firm belief , however , that if realized in real -time , this procedure will have a definite impact on the cotton cleaning process , and indeed on the economic value of cotton .
URI: http : / /hdl .handle .net /2346 /11201
Date: 2002-08

Citation

Pai, Ajay S X-ray microtomographic image analysis for identification of cotton contaminants. Master's thesis, Texas Tech University. Available electronically from http : / /hdl .handle .net /2346 /11201 .

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