一种有效地自动图像增强方法-外文文献翻译

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1、附录A：外文文献AnEffectiveAutomaticImageEnhancementMethodABSTRACTOtsumethodispropertodealwithtwoconditions:(1)twoormoreclasseswithdistintivegray-valuesrespectively;(2)classeswithoutdistinctivegray-values,butwithsimilarareas.However,whenthegray-valuedifferencesamongclassesarenotsodistinc

2、t,andtheobjectissmallrelativetobackgroud,theseparabilitiesamongclassesareinsufficient.Inordertoovercometheaboveproblem,thispaperpresentsanimprovedspatiallow-passfilterwithaparameterandpresentsanunsupervisedmethodofautomaticparameterselectionforimageenhancementbasedonOtsumethod.Th

3、ismethodcombinesimageenhancementwithimagesegmentationasoneprocedurethroughadiscriminantcriterion.Theoptimalparameterofthefilterisselectedbythediscriminantcriteriongiventomaximizetheseparabilitybetweenobjectandbackground.Theoptimalthresholdforimagesegmentationiscomputedsimultaneou

4、sly.Themethodisusedtodetectthesurfacedefectofcontainer.Experimentsillustratethevalidityofthemethod.KEYWORDSimageprocessing;automatedimageenhancement;imagesegmentation;automatedvisualinspection1IntroductionAutomatedvisualinspectionofcrackedcontainer(AVICC)isapracticalapplicationof

5、machinevisiontechnology.Torealizeourgoal,fouressentialoperationsmustbedealtwith–imagepreprocessing,objectdetection,featuredescriptionandfinalcrackedobjectclassification.Imageenhancementistoprovidearesultmoresuitablethanoriginalimageforspecificapplications.Inthispapertheobjectiveo

6、fenhancement,followedbyimagesegmentation,istoobtainanimagewithahighercontentabouttheobjectinterestingwithlesscontentaboutnoiseandbackground.Gonzalez[1]discussesthatimageenhancementapproachesfallintotwomaincategories,inthatspatialdomainandfrequencydomainmethods.Burton[2]appliesima

7、geaveragingtechniquetofacerecognitionsystem,makingitabletorecognisefamiliarfaceseasilyacrosslargevariationsinimagequality.Centeno[3]proposesanadaptiveimageenhancementalgorithm,whichreversetheprocessingorderofimageenhancementandsegmentationinordertoavoidsharpeningnoiseandblurringb

8、orders.Munteanu[4]appliesartificialintel