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1、ParticleSwarmOptimizationMethodsforPatternRecognitionandImageProcessingbyMahamedG.H.OmranSubmittedinpartialfulfillmentoftherequirementsforthedegreePhilosophiaeDoctorintheFacultyofEngineering,BuiltEnvironmentandInformationTechnologyUniversityofPretoriaPretoriaNovember2004
2、ParticleSwarmOptimizationMethodsforPatternRecognitionandImageProcessingbyMahamedG.H.OmranAbstractPatternrecognitionhasasitsobjectivetoclassifyobjectsintodifferentcategoriesandclasses.Itisafundamentalcomponentofartificialintelligenceandcomputervision.Thisthesisinvestigate
3、stheapplicationofanefficientoptimizationmethod,knownasParticleSwarmOptimization(PSO),tothefieldofpatternrecognitionandimageprocessing.FirstaclusteringmethodthatisbasedonPSOisproposed.Theapplicationoftheproposedclusteringalgorithmtotheproblemofunsupervisedclassificationan
4、dsegmentationofimagesisinvestigated.Anewautomaticimagegenerationtooltailoredspecificallyfortheverificationandcomparisonofvariousunsupervisedimageclassificationalgorithmsisthendeveloped.Adynamicclusteringalgorithmwhichautomaticallydeterminesthe"optimum"numberofclustersand
5、simultaneouslyclustersthedatasetwithminimaluserinterferenceisthendeveloped.Finally,PSO-basedapproachesareproposedtotacklethecolorimagequantizationandspectralunmixingproblems.Inalltheproposedapproaches,theinfluenceofPSOparametersontheperformanceoftheproposedalgorithmsisev
6、aluated.Keyterms:Clustering,ColorImageQuantization,DynamicClustering,ImageProcessing,ImageSegmentation,OptimizationMethods,ParticleSwarmOptimization,PatternRecognition,SpectralUnmixing,UnsupervisedImageClassification.Thesissupervisor:Prof.A.P.EngelbrechtThesisco-supervis
7、or:Dr.AyedSalmanDepartmentofComputerEngineering,KuwaitUniversity,KuwaitDepartmentofComputerScienceDegree:PhilosophiaeDoctorii“Obstaclesarethosefrighteningthingsyouseewhenyoutakeyoureyesoffyourgoal.”HenryFord“Youwillrecognizeyourownpathwhenyoucomeuponit,becauseyouwillsudd
8、enlyhavealltheenergyandimaginationyouwilleverneed.”JerryGilliesiiiAcknowledgmentsIaddressmysinceregrati
