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dc.contributor.authorKasam, Shashi Kanth
dc.description.abstractGlowworm Smarm Optimization (GSO), one of the nature-inspired swarm intelligence algorithms is used for finding solutions to optimization problems. Glowworms emit light to attract its mates and mates choosing the brighter member is the basis for this algorithm. We apply this algorithm in conjunction with traditional multi-threshold image segmentation by Otsu method to arrive at our results. The glowworm selection of mates and the movement of these has been mapped to a scientific algorithm to solve the problem and make multi-level threshold image segmentation a relatively efficient one. This algorithm has been implemented in MATLAB and the results are thus presented.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.titleGlowworm Swarm Optimization Algorithm for Multi-Threshold Image Segmentationen_US
dc.typeMaster's paperen_US
dc.date.accessioned2016-03-29T19:01:50Z
dc.date.available2016-03-29T19:01:50Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10365/25558
dc.subject.lcshEvolutionary computation.en_US
dc.subject.lcshImage segmentation.en_US
dc.subject.lcshSwarm intelligence.en_US
dc.subject.lcshComputational intelligence.en_US
dc.subject.lcshAlgorithms.en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US
ndsu.advisorLudwig, Simone


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