10.6. INTEGRATINGTHENEWTECHNIQUES
149
Figure10.23:ResultofEdgeandGrayShadeSegmentationofFigure10.4
alltheobjects are rightnext to each other and hardto distinguish. . The
combinationsegmentationinFigure10.26isanexcellentresult.Itdetected
objectsnotfound intheedge-only y techniqueandalso eliminatedmany of
theunwantedbricks.
10.6 IntegratingtheNewTechniques
Listing10.3showsthemain2segprogramforsegmentingentireimagesusing
thenewtechniques.Itiscommand-linedrivenandcallsthefunctionsgiven
inthepreviouslistings.Itfollowsthesamepatternasthemainsegprogram
ofchapter9andotherprogramsshowninthistext.
10.7 Conclusions
Thischapterdescribedthree powerfulimagesegmentationtechniquesthat
workoncomplicatedimages.Thetechniques,however,areonlycombinations
of existing tools andtricks. . Given n dierent images, youmight have used
dierentcombinationsoftools.Experiment,trydierentcombinations,and
modifyexistingtoolstocreatenewones.
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150 CHAPTER10. . SEGMENTATIONVIAEDGES&GRAYSHADES
Figure10.24:ResultofEdge-OnlySegmentationofFigure10.5
Figure10.25:ResultofGray-Shade-OnlySegmentationofFigure10.5
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10.8. REFERENCE
151
Figure10.26:ResultofEdgeandGrayShadeSegmentationofFigure10.5
10.8 Reference
10.1\TheImageProcessingHandbook,ThirdEdition,"JohnC.Russ,CRC
Press,1999.
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152 CHAPTER10. . SEGMENTATIONVIAEDGES&GRAYSHADES
VB.NET PowerPoint: Read & Scan Barcode Image from PPT Slide
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Chapter11
ManipulatingShapes
11.1 Introduction
This chapter willdiscuss manipulatingshapes. . Thelasttwochaptersdis-
cussed imagesegmentation. . Segmentationtook k an n imageandproduced a
binary output showing the objects ofinterest. . This s chapter willdescribe
severaltechniquesfortakingthoseobjectsandimprovingtheirappearance.
11.2 WorkingwithShapes
Amajorgoalofimageprocessingistoimprovetheappearanceofanimage.
Figure 11.1 shows s an n aerial image, and Figure 11.2 a segmentation of it.
Figure11.3showsahouse,andFigure11.4asegmentationofit. Theseare
goodsegmentations,buttheyhaveproblems.
Segmentationresultshave\holes"inthem.TheroofinFigure11.4should
besolid,buthasholes. Largerholescanevenbreakobjects. Theopposite
canalsobetrue,as segmentationcanjoinseparateobjects. . Segmentation
resultsoftenhavelittleornomeaning.Thesolidobjectsresembleblobsand
arehardtointerpret.
Theanswertotheseproblemsismorphologicallteringormanipulating
shapes. Usefultechniquesincludeerosionanddilation,openingandclosing,
outlining,andthinningandskeletonization.
Thesetechniquesworkonbinaryimageswheretheobjectequalsavalue
and the background d is s zero. . Figure e 11.5 5 shows a a binary y image e with the
backgroundequaltozeroandtheobjectequalto200.Alltheguresinthe
153
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154
CHAPTER11. MANIPULATINGSHAPES
Figure11.1: AerialImage
Figure11.2:SegmentationofAerialImage
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11.2. WORKINGWITHSHAPES
155
Figure11.3:HouseImage
Figure11.4:SegmentationofHouseImage
156
CHAPTER11. MANIPULATINGSHAPES
0
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Figure11.5:ABinaryImage
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Figure11.6:TheResultofErodingFigure11.5
chapterwillusethesameformat.
11.3 ErosionandDilation
Theerosionanddilationoperationsmakeobjectssmallerandlarger.These
operationsarevaluableinthemselvesandarethefoundationfortheopening
andclosingoperations. Erosion,discussedbrie y y inChapter10,makesan
objectsmallerbyremovingorerodingawaythepixelsonitsedges. Figure
11.6showstheresultoferodingtherectangleinFigure11.5.
Dilationmakesanobjectlargerbyaddingpixelsarounditsedges.Figure
11.3. EROSIONANDDILATION
157
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0 *** 200 200 0 200 200 0 200 200 ***
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0 *** 200 200 0 200 200 0 200 200 ***
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0 *** 200 200 0 200 200 0 200 200 ***
0
0 *** 200 200 0 200 200 0 200 200 ***
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0 *** *** *** * *** *** * *** *** ***
0
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Figure11.7: TheResultofDilatingFigure11.5
11.7showstheresultofdilatingtherectangleinFigure11.5. Isetanyzero
pixelthatwasnexttoa200pixel(shownasasterisks).
Therearetwogeneraltechniquesforerosionanddilation.Thetechnique
introducedinChapter10employsathreshold[11.1].Anothertechniqueuses
maskstoerodeanddilateindesireddirections[11.2].
The threshold techniquelooks atthe neighborsof apixelandchanges
its state if the number of dieringneighbors exceeds athreshold. . Listing
11.1showstheerosionanddilationroutinesthatusethismethod.Theloops
intheerosionroutineexamineeverypixelequaltovalueinthe
image. The
loopscountthenumberofzeroneighborsandsetthepixelinquestiontozero
ifthecountexceedsthethresholdparameter. Figure11.6usedathreshold
parameterofthree.ComparethistoFigure11.8(threshold=two).
Theloopsinthedilationroutinedotheopposite. Theycountthevalue
pixelsnexttoazeropixel.Ifthecountexceedsthethresholdparameter,set
thezeropixeltovalue. ThedilationinFigure11.7usedthreshold=three,
whileFigure11.9usedthreshold=two.
Themaskingtechnique[11.2]laysannxn(3x3,5x5,etc.) arrayof1sand
0s ontopofaninput imageanderodes ordilatestheinput. . Withmasks
youcancontrolthedirectionoferosionordilation.Figure11.10showsfour
3x3masks(5x5,7x7,etc.masksareotherpossibilities).Thersttwomasks
modify the e input t image e in n the e verticalor horizontaldirections while e the
secondtwoperforminbothdirections.
Figure11.11showstheresultsofdilatingtheobjectofFigure11.5using
thefourmasksofFigure11.10.Theprocedureis:
158
CHAPTER11. MANIPULATINGSHAPES
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Figure11.8:TheResultofErodingFigure11.5UsingaThresholdof2
0
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Figure11.9: TheResultofDilatingFigure11.5UsingaThresholdof2
vertical mask
horizontal mask
0 1 1 0
0 0 0 0
0 1 1 0
1 1 1 1
0 1 1 0
0 0 0 0
horizontal and d vertical masks
0 1 1 0
1 1 1 1
1 1 1 1
1 1 1 1
0 1 1 0
1 1 1 1
Figure11.10:Four3x3Masks
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