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dc.contributor.authorYang, Xinmin
dc.contributor.authorBeyenal, Haluk
dc.contributor.authorHarkin, Gary
dc.contributor.authorLewandowski, Zbigniew
dc.date.accessioned2017-09-12T21:39:31Z
dc.date.available2017-09-12T21:39:31Z
dc.date.issued2001-04
dc.identifier.citationXinmin, Y., H. Beyenal, G. Harkin, Z. Lewandowski, "Evaluation of Biofilm Image Thresholding Methods," Wat. Res., 35(5):118 (2001).en_US
dc.identifier.issn0043-1354
dc.identifier.urihttp://scholarworks.montana.edu/xmlui/handle/1/13635
dc.description.abstractTo evaluate biomass distribution in heterogeneous biofilms from their microscope images, it is often necessary to perform image thresholding by converting the gray-scale images to binary images consisting of a foreground of biomass material and a background of interstitial space. The selection of gray-scale intensity used for thresholding is arbitrary but under the control of the operator, which may produce unacceptable levels of variability among operators. The quality of numerical information extracted from the images is diminished by such variability, and it is desirable to find a method that improves the reproducibility of thresholding operation. Automatic methods of thresholding provide this reproducibility, but often at the expense of accuracy, as they consistently set thresholds that differ significantly from what human operators would chose. The performance of five automatic image thresholding algorithms was tested in this study; (1) local entropy; (2) joint entropy; (3) relative entropy; (4) Renyi’s entropy; and (5) iterative selection. Only the iterative selection method was satisfactory in that it was consistently setting the threshold level near that set manually. The extraction of feature information from biofilm images benefits from automatic thresholding and can be extended to other fields, such as medical imaging.en_US
dc.titleEvaluation of biofilm image thresholding methodsen_US
dc.typeArticleen_US
mus.citation.extentfirstpage1149en_US
mus.citation.extentlastpage1158en_US
mus.citation.issue5en_US
mus.citation.journaltitleWater Researchen_US
mus.citation.volume35en_US
mus.identifier.categoryEngineering & Computer Scienceen_US
mus.identifier.doi10.1016/s0043-1354(00)00361-4en_US
mus.relation.collegeCollege of Engineeringen_US
mus.relation.departmentCenter for Biofilm Engineering.en_US
mus.relation.departmentChemical & Biological Engineering.en_US
mus.relation.departmentChemical Engineering.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.relation.researchgroupCenter for Biofilm Engineering.en_US
mus.data.thumbpage8en_US


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